Cytomining Ecosystem Software Landscape Analysis: Data Profile

Dataset statistics

Number of variables	32
Number of observations	1121
Missing cells	2995
Missing cells (%)	8.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	265.3 KiB
Average record size in memory	242.3 B

Variable types

Text	5
Numeric	14
Unsupported	7
Categorical	3
DateTime	2
Boolean	1

Alerts

`GitHub Repo Archived` is highly imbalanced (89.8%)	Imbalance
`category` is highly imbalanced (75.3%)	Imbalance
`Project Homepage` has 536 (47.8%) missing values	Missing
`GitHub License Type` has 545 (48.6%) missing values	Missing
`GitHub Description` has 55 (4.9%) missing values	Missing
`GitHub Organization` has 726 (64.8%) missing values	Missing
`GitHub Stars (Log Scale)` has 40 (3.6%) missing values	Missing
`GitHub Forks (Log Scale)` has 426 (38.0%) missing values	Missing
`GitHub Open Issues (Log Scale)` has 667 (59.5%) missing values	Missing
`GitHub Stars` is highly skewed (γ1 = 21.38157534)	Skewed
`GitHub Forks` is highly skewed (γ1 = 25.16850093)	Skewed
`GitHub Subscribers` is highly skewed (γ1 = 22.74749218)	Skewed
`GitHub Network Count` is highly skewed (γ1 = 25.16825463)	Skewed
`total lines of GitHub detected code` is highly skewed (γ1 = 23.40119625)	Skewed
`GitHub Repository ID` has unique values	Unique
`Project Repo URL` has unique values	Unique
`Date Created` has unique values	Unique
`Date Most Recent Commit` has unique values	Unique
`Project Landscape Category` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`GitHub Topics` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`GitHub Detected Languages` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Duration Created to Most Recent Commit` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Duration Created to Now` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Duration Most Recent Commit to Now` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Negative Duration Most Recent Commit to Now` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`GitHub Stars` has 40 (3.6%) zeros	Zeros
`GitHub Forks` has 426 (38.0%) zeros	Zeros
`GitHub Subscribers` has 47 (4.2%) zeros	Zeros
`GitHub Open Issues` has 667 (59.5%) zeros	Zeros
`GitHub Contributors` has 28 (2.5%) zeros	Zeros
`GitHub Network Count` has 426 (38.0%) zeros	Zeros
`GitHub Stars (Log Scale)` has 297 (26.5%) zeros	Zeros
`GitHub Forks (Log Scale)` has 165 (14.7%) zeros	Zeros
`GitHub Open Issues (Log Scale)` has 127 (11.3%) zeros	Zeros

Reproduction

Analysis started	2023-11-29 00:29:29.992896
Analysis finished	2023-11-29 00:29:44.742156
Duration	14.75 seconds
Software version	ydata-profiling vv4.6.1
Download configuration	config.json

Project Name
Text

Distinct	1089
Distinct (%)	97.1%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Length

Max length	100
Median length	65
Mean length	14.947368
Min length	3

Characters and Unicode

Total characters	16756
Distinct characters	65
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1065 ?
Unique (%)	95.0%

Sample

1st row	pandas
2nd row	numpy
3rd row	duckdb
4th row	arrow
5th row	parquet-mr

Value	Count	Frequency (%)
single-cell-analysis	8	0.7%
single-cell-rna-seq-analysis	7	0.6%
single_cell_analysis	7	0.6%
singlecellanalysis	4	0.4%
singlecell	4	0.4%
single-cell-rna-seq	4	0.4%
orchestratingsinglecellanalysis	3	0.3%
scrna-seq	2	0.2%
single-cell-rna-sequencing-analysis	2	0.2%
scrnaseq	2	0.2%
Other values (1058)	1078	96.2%

Most occurring characters

Value	Count	Frequency (%)
e	1432	8.5%
l	1352	8.1%
s	1250	7.5%
i	1011	6.0%
a	1003	6.0%
n	939	5.6%
-	833	5.0%
c	772	4.6%
o	683	4.1%
t	600	3.6%
Other values (55)	6881	41.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12268	73.2%
Uppercase Letter	2813	16.8%
Dash Punctuation	833	5.0%
Connector Punctuation	425	2.5%
Decimal Number	397	2.4%
Other Punctuation	20	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1432	11.7%
l	1352	11.0%
s	1250	10.2%
i	1011	8.2%
a	1003	8.2%
n	939	7.7%
c	772	6.3%
o	683	5.6%
t	600	4.9%
r	568	4.6%
Other values (16)	2658	21.7%

Uppercase Letter

Value	Count	Frequency (%)
A	432	15.4%
C	393	14.0%
S	378	13.4%
R	227	8.1%
N	206	7.3%
M	134	4.8%
T	131	4.7%
P	126	4.5%
I	112	4.0%
D	101	3.6%
Other values (16)	573	20.4%

Decimal Number

Value	Count	Frequency (%)
2	151	38.0%
0	97	24.4%
1	67	16.9%
3	22	5.5%
9	19	4.8%
8	14	3.5%
4	10	2.5%
7	8	2.0%
6	5	1.3%
5	4	1.0%

Dash Punctuation

Value	Count	Frequency (%)
-	833	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	425	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	20	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	15081	90.0%
Common	1675	10.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1432	9.5%
l	1352	9.0%
s	1250	8.3%
i	1011	6.7%
a	1003	6.7%
n	939	6.2%
c	772	5.1%
o	683	4.5%
t	600	4.0%
r	568	3.8%
Other values (42)	5471	36.3%

Common

Value	Count	Frequency (%)
-	833	49.7%
_	425	25.4%
2	151	9.0%
0	97	5.8%
1	67	4.0%
3	22	1.3%
.	20	1.2%
9	19	1.1%
8	14	0.8%
4	10	0.6%
Other values (3)	17	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16756	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1432	8.5%
l	1352	8.1%
s	1250	7.5%
i	1011	6.0%
a	1003	6.0%
n	939	5.6%
-	833	5.0%
c	772	4.6%
o	683	4.1%
t	600	3.6%
Other values (55)	6881	41.1%

GitHub Repository ID
Real number (ℝ)

UNIQUE

Distinct	1121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.839268 × 10⁸

Minimum	858127
Maximum	7.2151952 × 10⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	858127
5-th percentile	50261918
Q1	1.4183365 × 10⁸
median	2.5505668 × 10⁸
Q3	3.9224795 × 10⁸
95-th percentile	6.2561219 × 10⁸
Maximum	7.2151952 × 10⁸
Range	7.2066139 × 10⁸
Interquartile range (IQR)	2.504143 × 10⁸

Descriptive statistics

Standard deviation	1.7567511 × 10⁸
Coefficient of variation (CV)	0.61873381
Kurtosis	-0.54298386
Mean	2.839268 × 10⁸
Median Absolute Deviation (MAD)	1.2265867 × 10⁸
Skewness	0.57851496
Sum	3.1828194 × 10¹¹
Variance	3.0861745 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
858127	1	0.1%
162697103	1	0.1%
705254694	1	0.1%
504734280	1	0.1%
514744648	1	0.1%
311841960	1	0.1%
290603264	1	0.1%
104008503	1	0.1%
234948204	1	0.1%
599584321	1	0.1%
Other values (1111)	1111	99.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
858127	1	0.1%
908607	1	0.1%
1571820	1	0.1%
2136580	1	0.1%
2290781	1	0.1%
2425273	1	0.1%
4890816	1	0.1%
5771522	1	0.1%
8678018	1	0.1%
9252402	1	0.1%

Value	Count	Frequency (%)
721519518	1	0.1%
719574464	1	0.1%
717731826	1	0.1%
714695155	1	0.1%
713184601	1	0.1%
705254694	1	0.1%
704625957	1	0.1%
704561629	1	0.1%
703064293	1	0.1%
700499845	1	0.1%

Project Homepage
Text

MISSING

Distinct	209
Distinct (%)	35.7%
Missing	536
Missing (%)	47.8%
Memory size	8.9 KiB

Length

Max length	116
Median length	0
Mean length	13.94188
Min length	0

Characters and Unicode

Total characters	8156
Distinct characters	65
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	207 ?
Unique (%)	35.4%

Sample

1st row	https://pandas.pydata.org
2nd row	https://numpy.org
3rd row	http://www.duckdb.org
4th row	https://arrow.apache.org/
5th row

Value	Count	Frequency (%)
http://nasqar.abudhabi.nyu.edu	2	1.0%
https://genocraft.stanford.edu	1	0.5%
https://pachterlab.github.io/kallisto	1	0.5%
http://www.duckdb.org	1	0.5%
https://arrow.apache.org	1	0.5%
https://snakemake.readthedocs.io	1	0.5%
http://www.satijalab.org/seurat	1	0.5%
https://napari.org	1	0.5%
https://scanpy.readthedocs.io	1	0.5%
http://scvi-tools.org	1	0.5%
Other values (198)	198	94.7%

Most occurring characters

Value	Count	Frequency (%)
t	770	9.4%
/	739	9.1%
s	496	6.1%
i	480	5.9%
o	468	5.7%
.	413	5.1%
h	413	5.1%
e	411	5.0%
a	374	4.6%
p	312	3.8%
Other values (55)	3280	40.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6160	75.5%
Other Punctuation	1359	16.7%
Decimal Number	293	3.6%
Uppercase Letter	201	2.5%
Dash Punctuation	124	1.5%
Connector Punctuation	17	0.2%
Open Punctuation	1	< 0.1%
Close Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	770	12.5%
s	496	8.1%
i	480	7.8%
o	468	7.6%
h	413	6.7%
e	411	6.7%
a	374	6.1%
p	312	5.1%
c	297	4.8%
r	293	4.8%
Other values (16)	1846	30.0%

Uppercase Letter

Value	Count	Frequency (%)
C	29	14.4%
S	27	13.4%
A	23	11.4%
R	16	8.0%
M	11	5.5%
T	10	5.0%
D	9	4.5%
O	9	4.5%
I	9	4.5%
N	9	4.5%
Other values (12)	49	24.4%

Decimal Number

Value	Count	Frequency (%)
1	64	21.8%
0	59	20.1%
2	42	14.3%
3	23	7.8%
4	22	7.5%
6	19	6.5%
8	17	5.8%
7	16	5.5%
9	16	5.5%
5	15	5.1%

Other Punctuation

Value	Count	Frequency (%)
/	739	54.4%
.	413	30.4%
:	207	15.2%

Dash Punctuation

Value	Count	Frequency (%)
-	124	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	17	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6361	78.0%
Common	1795	22.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	770	12.1%
s	496	7.8%
i	480	7.5%
o	468	7.4%
h	413	6.5%
e	411	6.5%
a	374	5.9%
p	312	4.9%
c	297	4.7%
r	293	4.6%
Other values (38)	2047	32.2%

Common

Value	Count	Frequency (%)
/	739	41.2%
.	413	23.0%
:	207	11.5%
-	124	6.9%
1	64	3.6%
0	59	3.3%
2	42	2.3%
3	23	1.3%
4	22	1.2%
6	19	1.1%
Other values (7)	83	4.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8156	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	770	9.4%
/	739	9.1%
s	496	6.1%
i	480	5.9%
o	468	5.7%
.	413	5.1%
h	413	5.1%
e	411	5.0%
a	374	4.6%
p	312	3.8%
Other values (55)	3280	40.2%

Project Repo URL
Text

UNIQUE

Distinct	1121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Length

Max length	134
Median length	90
Mean length	45.074933
Min length	28

Characters and Unicode

Total characters	50529
Distinct characters	67
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1121 ?
Unique (%)	100.0%

Sample

1st row	https://github.com/pandas-dev/pandas
2nd row	https://github.com/numpy/numpy
3rd row	https://github.com/duckdb/duckdb
4th row	https://github.com/apache/arrow
5th row	https://github.com/apache/parquet-mr

Value	Count	Frequency (%)
https://github.com/pandas-dev/pandas	1	0.1%
https://github.com/scverse/scanpy	1	0.1%
https://github.com/apache/arrow	1	0.1%
https://github.com/apache/parquet-mr	1	0.1%
https://github.com/snakemake/snakemake	1	0.1%
https://github.com/satijalab/seurat	1	0.1%
https://github.com/napari/napari	1	0.1%
https://github.com/chris-mcginnis-ucsf/doubletfinder	1	0.1%
https://github.com/theislab/single-cell-tutorial	1	0.1%
https://github.com/sqjin/cellchat	1	0.1%
Other values (1111)	1111	99.1%

Most occurring characters

Value	Count	Frequency (%)
/	4484	8.9%
t	4372	8.7%
i	3019	6.0%
s	2924	5.8%
h	2806	5.6%
o	2418	4.8%
c	2291	4.5%
a	2201	4.4%
e	2188	4.3%
l	1919	3.8%
Other values (57)	21907	43.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	37794	74.8%
Other Punctuation	6746	13.4%
Uppercase Letter	3743	7.4%
Dash Punctuation	1089	2.2%
Decimal Number	732	1.4%
Connector Punctuation	425	0.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	4372	11.6%
i	3019	8.0%
s	2924	7.7%
h	2806	7.4%
o	2418	6.4%
c	2291	6.1%
a	2201	5.8%
e	2188	5.8%
l	1919	5.1%
g	1818	4.8%
Other values (16)	11838	31.3%

Uppercase Letter

Value	Count	Frequency (%)
A	481	12.9%
C	465	12.4%
S	453	12.1%
R	251	6.7%
N	236	6.3%
M	196	5.2%
L	180	4.8%
T	177	4.7%
I	156	4.2%
P	155	4.1%
Other values (16)	993	26.5%

Decimal Number

Value	Count	Frequency (%)
2	196	26.8%
0	151	20.6%
1	126	17.2%
9	54	7.4%
3	46	6.3%
8	42	5.7%
4	36	4.9%
7	32	4.4%
5	26	3.6%
6	23	3.1%

Other Punctuation

Value	Count	Frequency (%)
/	4484	66.5%
.	1141	16.9%
:	1121	16.6%

Dash Punctuation

Value	Count	Frequency (%)
-	1089	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	425	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	41537	82.2%
Common	8992	17.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	4372	10.5%
i	3019	7.3%
s	2924	7.0%
h	2806	6.8%
o	2418	5.8%
c	2291	5.5%
a	2201	5.3%
e	2188	5.3%
l	1919	4.6%
g	1818	4.4%
Other values (42)	15581	37.5%

Common

Value	Count	Frequency (%)
/	4484	49.9%
.	1141	12.7%
:	1121	12.5%
-	1089	12.1%
_	425	4.7%
2	196	2.2%
0	151	1.7%
1	126	1.4%
9	54	0.6%
3	46	0.5%
Other values (5)	159	1.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	50529	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
/	4484	8.9%
t	4372	8.7%
i	3019	6.0%
s	2924	5.8%
h	2806	5.6%
o	2418	4.8%
c	2291	4.5%
a	2201	4.4%
e	2188	4.3%
l	1919	3.8%
Other values (57)	21907	43.4%

Project Landscape Category
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

GitHub Stars
Real number (ℝ)

SKEWED ZEROS

Distinct	161
Distinct (%)	14.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	121.61106

Minimum	0
Maximum	40456
Zeros	40
Zeros (%)	3.6%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	3
Q3	17
95-th percentile	197
Maximum	40456
Range	40456
Interquartile range (IQR)	16

Descriptive statistics

Standard deviation	1529.0813
Coefficient of variation (CV)	12.573538
Kurtosis	504.31912
Mean	121.61106
Median Absolute Deviation (MAD)	2
Skewness	21.381575
Sum	136326
Variance	2338089.7
Monotonicity	Decreasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	297	26.5%
2	136	12.1%
3	89	7.9%
4	68	6.1%
5	42	3.7%
0	40	3.6%
6	28	2.5%
7	22	2.0%
8	20	1.8%
9	18	1.6%
Other values (151)	361	32.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	40	3.6%
1	297	26.5%
2	136	12.1%
3	89	7.9%
4	68	6.1%
5	42	3.7%
6	28	2.5%
7	22	2.0%
8	20	1.8%
9	18	1.6%

Value	Count	Frequency (%)
40456	1	0.1%
25080	1	0.1%
13165	1	0.1%
12804	1	0.1%
2230	1	0.1%
1990	1	0.1%
1987	1	0.1%
1953	1	0.1%
1645	1	0.1%
1623	1	0.1%

GitHub Forks
Real number (ℝ)

SKEWED ZEROS

Distinct	96
Distinct (%)	8.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	39.633363

Minimum	0
Maximum	16945
Zeros	426
Zeros (%)	38.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	6
95-th percentile	54
Maximum	16945
Range	16945
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	582.05691
Coefficient of variation (CV)	14.686034
Kurtosis	683.54322
Mean	39.633363
Median Absolute Deviation (MAD)	1
Skewness	25.168501
Sum	44429
Variance	338790.25
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	426	38.0%
1	165	14.7%
2	107	9.5%
3	59	5.3%
4	44	3.9%
5	36	3.2%
6	25	2.2%
8	24	2.1%
7	20	1.8%
9	15	1.3%
Other values (86)	200	17.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	426	38.0%
1	165	14.7%
2	107	9.5%
3	59	5.3%
4	44	3.9%
5	36	3.2%
6	25	2.2%
7	20	1.8%
8	24	2.1%
9	15	1.3%

Value	Count	Frequency (%)
16945	1	0.1%
8845	1	0.1%
3140	1	0.1%
1341	1	0.1%
1223	1	0.1%
851	1	0.1%
543	1	0.1%
479	1	0.1%
478	1	0.1%
430	1	0.1%

GitHub Subscribers
Real number (ℝ)

SKEWED ZEROS

Distinct	47
Distinct (%)	4.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.2604817

Minimum	0
Maximum	1122
Zeros	47
Zeros (%)	4.2%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	2
Q3	4
95-th percentile	15
Maximum	1122
Range	1122
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	40.10947
Coefficient of variation (CV)	6.4067706
Kurtosis	581.58219
Mean	6.2604817
Median Absolute Deviation (MAD)	1
Skewness	22.747492
Sum	7018
Variance	1608.7696
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
1	360	32.1%
2	252	22.5%
3	113	10.1%
4	75	6.7%
0	47	4.2%
5	46	4.1%
6	41	3.7%
7	34	3.0%
8	24	2.1%
9	20	1.8%
Other values (37)	109	9.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	47	4.2%
1	360	32.1%
2	252	22.5%
3	113	10.1%
4	75	6.7%
5	46	4.1%
6	41	3.7%
7	34	3.0%
8	24	2.1%
9	20	1.8%

Value	Count	Frequency (%)
1122	1	0.1%
596	1	0.1%
351	1	0.1%
159	1	0.1%
95	1	0.1%
87	1	0.1%
79	1	0.1%
54	1	0.1%
52	1	0.1%
49	1	0.1%

GitHub Open Issues
Real number (ℝ)

ZEROS

Distinct	77
Distinct (%)	6.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18.791258

Minimum	0
Maximum	4075
Zeros	667
Zeros (%)	59.5%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	33
Maximum	4075
Range	4075
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	184.07387
Coefficient of variation (CV)	9.7957183
Kurtosis	358.75184
Mean	18.791258
Median Absolute Deviation (MAD)	0
Skewness	18.083082
Sum	21065
Variance	33883.189
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	667	59.5%
1	127	11.3%
2	52	4.6%
3	33	2.9%
4	31	2.8%
6	21	1.9%
7	16	1.4%
5	14	1.2%
8	12	1.1%
19	8	0.7%
Other values (67)	140	12.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	667	59.5%
1	127	11.3%
2	52	4.6%
3	33	2.9%
4	31	2.8%
5	14	1.2%
6	21	1.9%
7	16	1.4%
8	12	1.1%
9	7	0.6%

Value	Count	Frequency (%)
4075	1	0.1%
3617	1	0.1%
2189	1	0.1%
1045	1	0.1%
921	1	0.1%
727	1	0.1%
540	1	0.1%
435	1	0.1%
375	1	0.1%
310	1	0.1%

GitHub Contributors
Real number (ℝ)

ZEROS

Distinct	39
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.6503122

Minimum	0
Maximum	433
Zeros	28
Zeros (%)	2.5%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	3
95-th percentile	10
Maximum	433
Range	433
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	25.631505
Coefficient of variation (CV)	5.5117815
Kurtosis	186.6691
Mean	4.6503122
Median Absolute Deviation (MAD)	0
Skewness	13.069769
Sum	5213
Variance	656.97404
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=39)

Value	Count	Frequency (%)
1	657	58.6%
2	141	12.6%
3	99	8.8%
4	62	5.5%
5	31	2.8%
0	28	2.5%
6	17	1.5%
11	11	1.0%
7	10	0.9%
9	9	0.8%
Other values (29)	56	5.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	28	2.5%
1	657	58.6%
2	141	12.6%
3	99	8.8%
4	62	5.5%
5	31	2.8%
6	17	1.5%
7	10	0.9%
8	8	0.7%
9	9	0.8%

Value	Count	Frequency (%)
433	1	0.1%
412	1	0.1%
370	1	0.1%
282	1	0.1%
260	1	0.1%
192	1	0.1%
149	1	0.1%
128	1	0.1%
88	1	0.1%
82	1	0.1%

GitHub License Type
Categorical

MISSING

Distinct	15
Distinct (%)	2.6%
Missing	545
Missing (%)	48.6%
Memory size	8.9 KiB

MIT	215
GPL-3.0	164
NOASSERTION	75
BSD-3-Clause	47
Apache-2.0	28
Other values (10)	47

Length

Max length	18
Median length	12
Mean length	6.7065972
Min length	3

Characters and Unicode

Total characters	3863
Distinct characters	36
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	0.7%

Sample

1st row	BSD-3-Clause
2nd row	BSD-3-Clause
3rd row	MIT
4th row	Apache-2.0
5th row	Apache-2.0

Common Values

Value	Count	Frequency (%)
MIT	215	19.2%
GPL-3.0	164	14.6%
NOASSERTION	75	6.7%
BSD-3-Clause	47	4.2%
Apache-2.0	28	2.5%
CC0-1.0	13	1.2%
AGPL-3.0	9	0.8%
BSD-2-Clause	7	0.6%
GPL-2.0	7	0.6%
LGPL-3.0	4	0.4%
Other values (5)	7	0.6%
(Missing)	545	48.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mit	215	37.3%
gpl-3.0	164	28.5%
noassertion	75	13.0%
bsd-3-clause	47	8.2%
apache-2.0	28	4.9%
cc0-1.0	13	2.3%
agpl-3.0	9	1.6%
bsd-2-clause	7	1.2%
gpl-2.0	7	1.2%
lgpl-3.0	4	0.7%
Other values (5)	7	1.2%

Most occurring characters

Value	Count	Frequency (%)
-	344	8.9%
I	290	7.5%
T	290	7.5%
0	243	6.3%
.	230	6.0%
3	225	5.8%
M	216	5.6%
S	205	5.3%
L	189	4.9%
P	185	4.8%
Other values (26)	1446	37.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	2327	60.2%
Decimal Number	528	13.7%
Lowercase Letter	434	11.2%
Dash Punctuation	344	8.9%
Other Punctuation	230	6.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	290	12.5%
T	290	12.5%
M	216	9.3%
S	205	8.8%
L	189	8.1%
P	185	8.0%
G	184	7.9%
N	150	6.4%
O	150	6.4%
A	113	4.9%
Other values (7)	355	15.3%

Lowercase Letter

Value	Count	Frequency (%)
e	86	19.8%
a	84	19.4%
l	57	13.1%
s	57	13.1%
u	55	12.7%
c	30	6.9%
h	28	6.5%
p	28	6.5%
i	3	0.7%
r	2	0.5%
Other values (2)	4	0.9%

Decimal Number

Value	Count	Frequency (%)
0	243	46.0%
3	225	42.6%
2	44	8.3%
1	13	2.5%
4	3	0.6%

Dash Punctuation

Value	Count	Frequency (%)
-	344	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	230	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2761	71.5%
Common	1102	28.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
I	290	10.5%
T	290	10.5%
M	216	7.8%
S	205	7.4%
L	189	6.8%
P	185	6.7%
G	184	6.7%
N	150	5.4%
O	150	5.4%
A	113	4.1%
Other values (19)	789	28.6%

Common

Value	Count	Frequency (%)
-	344	31.2%
0	243	22.1%
.	230	20.9%
3	225	20.4%
2	44	4.0%
1	13	1.2%
4	3	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3863	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	344	8.9%
I	290	7.5%
T	290	7.5%
0	243	6.3%
.	230	6.0%
3	225	5.8%
M	216	5.6%
S	205	5.3%
L	189	4.9%
P	185	4.8%
Other values (26)	1446	37.4%

GitHub Description
Text

MISSING

Distinct	1054
Distinct (%)	98.9%
Missing	55
Missing (%)	4.9%
Memory size	8.9 KiB

Length

Max length	10997
Median length	339
Mean length	131.58724
Min length	7

Characters and Unicode

Total characters	140272
Distinct characters	109
Distinct categories	16 ?
Distinct scripts	5 ?
Distinct blocks	6 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1042 ?
Unique (%)	97.7%

Sample

1st row	Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
2nd row	The fundamental package for scientific computing with Python.
3rd row	DuckDB is an in-process SQL OLAP Database Management System
4th row	Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
5th row	Apache Parquet

Value	Count	Frequency (%)
analysis	943	4.8%
of	770	3.9%
and	656	3.3%
for	651	3.3%
the	636	3.2%
cell	509	2.6%
single-cell	473	2.4%
data	448	2.3%
single	391	2.0%
a	354	1.8%
Other values (3933)	13821	70.3%

Most occurring characters

Value	Count	Frequency (%)
	18766	13.4%
e	12404	8.8%
a	9762	7.0%
i	9625	6.9%
n	8673	6.2%
s	8562	6.1%
l	8141	5.8%
o	7743	5.5%
t	7692	5.5%
r	6048	4.3%
Other values (99)	42856	30.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	109323	77.9%
Space Separator	18766	13.4%
Uppercase Letter	6987	5.0%
Other Punctuation	2128	1.5%
Dash Punctuation	1289	0.9%
Decimal Number	1181	0.8%
Close Punctuation	228	0.2%
Open Punctuation	223	0.2%
Math Symbol	51	< 0.1%
Final Punctuation	40	< 0.1%
Other values (6)	56	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	12404	11.3%
a	9762	8.9%
i	9625	8.8%
n	8673	7.9%
s	8562	7.8%
l	8141	7.4%
o	7743	7.1%
t	7692	7.0%
r	6048	5.5%
c	4854	4.4%
Other values (19)	25819	23.6%

Uppercase Letter

Value	Count	Frequency (%)
A	1096	15.7%
S	766	11.0%
R	712	10.2%
C	700	10.0%
N	596	8.5%
T	396	5.7%
D	346	5.0%
P	323	4.6%
I	312	4.5%
M	278	4.0%
Other values (16)	1462	20.9%

Other Punctuation

Value	Count	Frequency (%)
.	883	41.5%
,	620	29.1%
:	175	8.2%
/	160	7.5%
"	157	7.4%
%	40	1.9%
'	36	1.7%
;	19	0.9%
&	13	0.6%
@	7	0.3%
Other values (4)	18	0.8%

Other Symbol

Value	Count	Frequency (%)
▪	6	37.5%
🌸	1	6.2%
🐟	1	6.2%
🏔	1	6.2%
🌍	1	6.2%
🍱	1	6.2%
🍣	1	6.2%
🧬	1	6.2%
🦀	1	6.2%
🧫	1	6.2%

Decimal Number

Value	Count	Frequency (%)
2	262	22.2%
0	255	21.6%
1	202	17.1%
3	87	7.4%
9	84	7.1%
5	70	5.9%
7	69	5.8%
4	61	5.2%
8	47	4.0%
6	44	3.7%

Math Symbol

Value	Count	Frequency (%)
=	22	43.1%
+	15	29.4%
>	9	17.6%
<	4	7.8%
~	1	2.0%

Dash Punctuation

Value	Count	Frequency (%)
-	1288	99.9%
–	1	0.1%

Close Punctuation

Value	Count	Frequency (%)
)	225	98.7%
]	3	1.3%

Open Punctuation

Value	Count	Frequency (%)
(	220	98.7%
[	3	1.3%

Final Punctuation

Value	Count	Frequency (%)
’	32	80.0%
”	8	20.0%

Space Separator

Value	Count	Frequency (%)
	18766	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	29	100.0%

Initial Punctuation

Value	Count	Frequency (%)
“	8	100.0%

Nonspacing Mark

Value	Count	Frequency (%)
️	1	100.0%

Other Letter

Value	Count	Frequency (%)
桜	1	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	116309	82.9%
Common	23960	17.1%
Inherited	1	< 0.1%
Han	1	< 0.1%
Greek	1	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	12404	10.7%
a	9762	8.4%
i	9625	8.3%
n	8673	7.5%
s	8562	7.4%
l	8141	7.0%
o	7743	6.7%
t	7692	6.6%
r	6048	5.2%
c	4854	4.2%
Other values (44)	32805	28.2%

Common

Value	Count	Frequency (%)
	18766	78.3%
-	1288	5.4%
.	883	3.7%
,	620	2.6%
2	262	1.1%
0	255	1.1%
)	225	0.9%
(	220	0.9%
1	202	0.8%
:	175	0.7%
Other values (42)	1064	4.4%

Inherited

Value	Count	Frequency (%)
️	1	100.0%

Han

Value	Count	Frequency (%)
桜	1	100.0%

Greek

Value	Count	Frequency (%)
α	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	140201	99.9%
Punctuation	49	< 0.1%
None	14	< 0.1%
Geometric Shapes	6	< 0.1%
VS	1	< 0.1%
CJK	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	18766	13.4%
e	12404	8.8%
a	9762	7.0%
i	9625	6.9%
n	8673	6.2%
s	8562	6.1%
l	8141	5.8%
o	7743	5.5%
t	7692	5.5%
r	6048	4.3%
Other values (79)	42785	30.5%

Punctuation

Value	Count	Frequency (%)
’	32	65.3%
”	8	16.3%
“	8	16.3%
–	1	2.0%

Geometric Shapes

Value	Count	Frequency (%)
▪	6	100.0%

None

Value	Count	Frequency (%)
ü	2	14.3%
🌸	1	7.1%
🐟	1	7.1%
🏔	1	7.1%
🌍	1	7.1%
🍱	1	7.1%
🍣	1	7.1%
🧬	1	7.1%
é	1	7.1%
🦀	1	7.1%
Other values (3)	3	21.4%

VS

Value	Count	Frequency (%)
️	1	100.0%

CJK

Value	Count	Frequency (%)
桜	1	100.0%

GitHub Topics
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

GitHub Organization
Text

MISSING

Distinct	265
Distinct (%)	67.1%
Missing	726
Missing (%)	64.8%
Memory size	8.9 KiB

Length

Max length	35
Median length	27
Mean length	11.458228
Min length	3

Characters and Unicode

Total characters	4526
Distinct characters	57
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	205 ?
Unique (%)	51.9%

Sample

1st row	pandas-dev
2nd row	numpy
3rd row	duckdb
4th row	apache
5th row	apache

Value	Count	Frequency (%)
theislab	13	3.3%
ucdavis-bioinformatics-training	9	2.3%
teichlab	8	2.0%
broadinstitute	7	1.8%
scverse	6	1.5%
cytomining	5	1.3%
kharchenkolab	5	1.3%
oshlack	5	1.3%
immunogenomics	5	1.3%
icbi-lab	5	1.3%
Other values (255)	327	82.8%

Most occurring characters

Value	Count	Frequency (%)
a	480	10.6%
i	362	8.0%
e	325	7.2%
b	295	6.5%
l	283	6.3%
n	276	6.1%
o	258	5.7%
s	252	5.6%
r	208	4.6%
c	195	4.3%
Other values (47)	1592	35.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3894	86.0%
Uppercase Letter	459	10.1%
Dash Punctuation	158	3.5%
Decimal Number	15	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	480	12.3%
i	362	9.3%
e	325	8.3%
b	295	7.6%
l	283	7.3%
n	276	7.1%
o	258	6.6%
s	252	6.5%
r	208	5.3%
c	195	5.0%
Other values (16)	960	24.7%

Uppercase Letter

Value	Count	Frequency (%)
L	73	15.9%
C	46	10.0%
B	45	9.8%
S	34	7.4%
M	32	7.0%
I	30	6.5%
G	22	4.8%
T	21	4.6%
R	18	3.9%
A	18	3.9%
Other values (14)	120	26.1%

Decimal Number

Value	Count	Frequency (%)
1	4	26.7%
0	4	26.7%
2	3	20.0%
4	2	13.3%
9	1	6.7%
3	1	6.7%

Dash Punctuation

Value	Count	Frequency (%)
-	158	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4353	96.2%
Common	173	3.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	480	11.0%
i	362	8.3%
e	325	7.5%
b	295	6.8%
l	283	6.5%
n	276	6.3%
o	258	5.9%
s	252	5.8%
r	208	4.8%
c	195	4.5%
Other values (40)	1419	32.6%

Common

Value	Count	Frequency (%)
-	158	91.3%
1	4	2.3%
0	4	2.3%
2	3	1.7%
4	2	1.2%
9	1	0.6%
3	1	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4526	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	480	10.6%
i	362	8.0%
e	325	7.2%
b	295	6.5%
l	283	6.3%
n	276	6.1%
o	258	5.7%
s	252	5.6%
r	208	4.6%
c	195	4.3%
Other values (47)	1592	35.2%

GitHub Network Count
Real number (ℝ)

SKEWED ZEROS

Distinct	97
Distinct (%)	8.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	39.695807

Minimum	0
Maximum	16945
Zeros	426
Zeros (%)	38.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	6
95-th percentile	55
Maximum	16945
Range	16945
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	582.05633
Coefficient of variation (CV)	14.662917
Kurtosis	683.53513
Mean	39.695807
Median Absolute Deviation (MAD)	1
Skewness	25.168255
Sum	44499
Variance	338789.57
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	426	38.0%
1	164	14.6%
2	107	9.5%
3	59	5.3%
4	44	3.9%
5	36	3.2%
6	25	2.2%
8	24	2.1%
7	19	1.7%
9	16	1.4%
Other values (87)	201	17.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	426	38.0%
1	164	14.6%
2	107	9.5%
3	59	5.3%
4	44	3.9%
5	36	3.2%
6	25	2.2%
7	19	1.7%
8	24	2.1%
9	16	1.4%

Value	Count	Frequency (%)
16945	1	0.1%
8845	1	0.1%
3140	1	0.1%
1341	1	0.1%
1223	1	0.1%
851	1	0.1%
543	1	0.1%
479	1	0.1%
478	1	0.1%
430	1	0.1%

GitHub Detected Languages
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Date Created
Date

UNIQUE

Distinct	1121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Minimum	2010-08-24 01:37:33+00:00
Maximum	2023-11-21 08:26:43+00:00

Histogram

Histogram with fixed size bins (bins=50)

Date Most Recent Commit
Date

UNIQUE

Distinct	1121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Minimum	2013-03-09 23:45:10+00:00
Maximum	2023-11-28 23:41:39+00:00

Histogram

Histogram with fixed size bins (bins=50)

Duration Created to Most Recent Commit
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Duration Created to Now
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Duration Most Recent Commit to Now
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Repository Size (KB)
Real number (ℝ)

Distinct	1016
Distinct (%)	90.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	78842.229

Minimum	1
Maximum	2073829
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	1
5-th percentile	16
Q1	749
median	10881
Q3	72368
95-th percentile	365804
Maximum	2073829
Range	2073828
Interquartile range (IQR)	71619

Descriptive statistics

Standard deviation	196928.54
Coefficient of variation (CV)	2.4977546
Kurtosis	41.356973
Mean	78842.229
Median Absolute Deviation (MAD)	10847
Skewness	5.6659771
Sum	88382139
Variance	3.8780851 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	10	0.9%
16	7	0.6%
24	6	0.5%
3	6	0.5%
9	5	0.4%
26	5	0.4%
13	5	0.4%
30	4	0.4%
22	4	0.4%
67	4	0.4%
Other values (1006)	1065	95.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2	0.2%
2	3	0.3%
3	6	0.5%
4	3	0.3%
5	3	0.3%
6	10	0.9%
7	2	0.2%
8	3	0.3%
9	5	0.4%
10	1	0.1%

Value	Count	Frequency (%)
2073829	1	0.1%
1971038	1	0.1%
1921765	1	0.1%
1792729	1	0.1%
1590023	1	0.1%
1496132	1	0.1%
1461986	1	0.1%
1447466	1	0.1%
1293566	1	0.1%
1245051	1	0.1%

GitHub Repo Archived
Boolean

IMBALANCE

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.2 KiB

False	1106
True	15

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	1106	98.7%
True	15	1.3%

Duration Created to Now in Years
Real number (ℝ)

Distinct	905
Distinct (%)	80.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.9164127

Minimum	0.019178082
Maximum	13.271233
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0.019178082
5-th percentile	0.63835616
Q1	2.3205479
median	3.630137
Q3	5.3589041
95-th percentile	7.8520548
Maximum	13.271233
Range	13.252055
Interquartile range (IQR)	3.0383562

Descriptive statistics

Standard deviation	2.268001
Coefficient of variation (CV)	0.57910164
Kurtosis	0.66876272
Mean	3.9164127
Median Absolute Deviation (MAD)	1.4657534
Skewness	0.70701185
Sum	4390.2986
Variance	5.1438287
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.816438356	5	0.4%
4.279452055	4	0.4%
3.334246575	4	0.4%
3.895890411	4	0.4%
6.369863014	3	0.3%
4.843835616	3	0.3%
2.169863014	3	0.3%
5.517808219	3	0.3%
4.04109589	3	0.3%
4.654794521	3	0.3%
Other values (895)	1086	96.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.01917808219	1	0.1%
0.03287671233	1	0.1%
0.04383561644	1	0.1%
0.06301369863	1	0.1%
0.07123287671	1	0.1%
0.1205479452	1	0.1%
0.1260273973	2	0.2%
0.1342465753	1	0.1%
0.1506849315	1	0.1%
0.1616438356	1	0.1%

Value	Count	Frequency (%)
13.27123288	1	0.1%
13.21643836	1	0.1%
12.65753425	1	0.1%
12.33424658	1	0.1%
12.25753425	1	0.1%
12.19726027	1	0.1%
11.40821918	1	0.1%
11.21917808	1	0.1%
10.7260274	1	0.1%
10.65479452	1	0.1%

Negative Duration Most Recent Commit to Now
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

category
Categorical

IMBALANCE

Distinct	5
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	1.4 KiB

github-query-result	1003
adjacent-tools	100
relevant-open-source	8
microscopy-analysis-tools	7
loi-focus	3

Length

Max length	25
Median length	19
Mean length	18.571811
Min length	9

Characters and Unicode

Total characters	20819
Distinct characters	23
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	relevant-open-source
2nd row	relevant-open-source
3rd row	relevant-open-source
4th row	relevant-open-source
5th row	relevant-open-source

Common Values

Value	Count	Frequency (%)
github-query-result	1003	89.5%
adjacent-tools	100	8.9%
relevant-open-source	8	0.7%
microscopy-analysis-tools	7	0.6%
loi-focus	3	0.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
github-query-result	1003	89.5%
adjacent-tools	100	8.9%
relevant-open-source	8	0.7%
microscopy-analysis-tools	7	0.6%
loi-focus	3	0.3%

Most occurring characters

Value	Count	Frequency (%)
u	3020	14.5%
t	2221	10.7%
-	2139	10.3%
e	2138	10.3%
r	2029	9.7%
s	1142	5.5%
l	1128	5.4%
i	1020	4.9%
y	1017	4.9%
g	1003	4.8%
Other values (13)	3962	19.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	18680	89.7%
Dash Punctuation	2139	10.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	3020	16.2%
t	2221	11.9%
e	2138	11.4%
r	2029	10.9%
s	1142	6.1%
l	1128	6.0%
i	1020	5.5%
y	1017	5.4%
g	1003	5.4%
q	1003	5.4%
Other values (12)	2959	15.8%

Dash Punctuation

Value	Count	Frequency (%)
-	2139	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	18680	89.7%
Common	2139	10.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	3020	16.2%
t	2221	11.9%
e	2138	11.4%
r	2029	10.9%
s	1142	6.1%
l	1128	6.0%
i	1020	5.5%
y	1017	5.4%
g	1003	5.4%
q	1003	5.4%
Other values (12)	2959	15.8%

Common

Value	Count	Frequency (%)
-	2139	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	20819	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
u	3020	14.5%
t	2221	10.7%
-	2139	10.3%
e	2138	10.3%
r	2029	9.7%
s	1142	5.5%
l	1128	5.4%
i	1020	4.9%
y	1017	4.9%
g	1003	4.8%
Other values (13)	3962	19.0%

GitHub Stars (Log Scale)
Real number (ℝ)

MISSING ZEROS

Distinct	160
Distinct (%)	14.8%
Missing	40
Missing (%)	3.6%
Infinite	0
Infinite (%)	0.0%
Mean	1.7924966

Minimum	0
Maximum	10.60797
Zeros	297
Zeros (%)	26.5%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1.3862944
Q3	2.8903718
95-th percentile	5.370638
Maximum	10.60797
Range	10.60797
Interquartile range (IQR)	2.8903718

Descriptive statistics

Standard deviation	1.7877632
Coefficient of variation (CV)	0.9973593
Kurtosis	1.3131191
Mean	1.7924966
Median Absolute Deviation (MAD)	1.3862944
Skewness	1.1406396
Sum	1937.6888
Variance	3.1960971
Monotonicity	Decreasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	297	26.5%
0.6931471806	136	12.1%
1.098612289	89	7.9%
1.386294361	68	6.1%
1.609437912	42	3.7%
1.791759469	28	2.5%
1.945910149	22	2.0%
2.079441542	20	1.8%
2.197224577	18	1.6%
2.302585093	15	1.3%
Other values (150)	346	30.9%
(Missing)	40	3.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	297	26.5%
0.6931471806	136	12.1%
1.098612289	89	7.9%
1.386294361	68	6.1%
1.609437912	42	3.7%
1.791759469	28	2.5%
1.945910149	22	2.0%
2.079441542	20	1.8%
2.197224577	18	1.6%
2.302585093	15	1.3%

Value	Count	Frequency (%)
10.60797024	1	0.1%
10.12982599	1	0.1%
9.485317072	1	0.1%
9.457512901	1	0.1%
7.709756864	1	0.1%
7.595889918	1	0.1%
7.594381243	1	0.1%
7.577121931	1	0.1%
7.405495663	1	0.1%
7.392031568	1	0.1%

total lines of GitHub detected code
Real number (ℝ)

SKEWED

Distinct	1115
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9843389.8

Minimum	101
Maximum	2.2291975 × 10⁹
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	101
5-th percentile	6099
Q1	46684
median	204987
Q3	1622642
95-th percentile	33306521
Maximum	2.2291975 × 10⁹
Range	2.2291974 × 10⁹
Interquartile range (IQR)	1575958

Descriptive statistics

Standard deviation	76661031
Coefficient of variation (CV)	7.7880723
Kurtosis	644.12398
Mean	9843389.8
Median Absolute Deviation (MAD)	191998
Skewness	23.401196
Sum	1.103444 × 10¹⁰
Variance	5.8769137 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
954832	4	0.4%
3354	2	0.2%
102304	2	0.2%
7465	2	0.2%
22861512	1	0.1%
906018	1	0.1%
1419408	1	0.1%
212785	1	0.1%
30183	1	0.1%
35920563	1	0.1%
Other values (1105)	1105	98.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
101	1	0.1%
397	1	0.1%
508	1	0.1%
547	1	0.1%
587	1	0.1%
695	1	0.1%
968	1	0.1%
1120	1	0.1%
1203	1	0.1%
1346	1	0.1%

Value	Count	Frequency (%)
2229197511	1	0.1%
880847605	1	0.1%
463016008	1	0.1%
280960563	1	0.1%
277061560	1	0.1%
232185079	1	0.1%
192917347	1	0.1%
183885622	1	0.1%
182341397	1	0.1%
178105096	1	0.1%

total lines of GitHub detected code (Log Scale)
Real number (ℝ)

Distinct	1115
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.589924

Minimum	4.6151205
Maximum	21.524907
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	4.6151205
5-th percentile	8.7158801
Q1	10.751157
median	12.230702
Q3	14.299566
95-th percentile	17.321264
Maximum	21.524907
Range	16.909787
Interquartile range (IQR)	3.5484095

Descriptive statistics

Standard deviation	2.6413136
Coefficient of variation (CV)	0.20979584
Kurtosis	-0.19287438
Mean	12.589924
Median Absolute Deviation (MAD)	1.6578988
Skewness	0.37880547
Sum	14113.304
Variance	6.9765376
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13.76929069	4	0.4%
8.117908942	2	0.2%
11.53570405	2	0.2%
8.91798071	2	0.2%
16.94496536	1	0.1%
13.71681445	1	0.1%
14.16575044	1	0.1%
12.26803755	1	0.1%
10.31503413	1	0.1%
17.39682047	1	0.1%
Other values (1105)	1105	98.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4.615120517	1	0.1%
5.983936281	1	0.1%
6.230481448	1	0.1%
6.304448802	1	0.1%
6.37502482	1	0.1%
6.543911846	1	0.1%
6.875232087	1	0.1%
7.021083964	1	0.1%
7.092573716	1	0.1%
7.20489251	1	0.1%

Value	Count	Frequency (%)
21.5249075	1	0.1%
20.59639519	1	0.1%
19.95327219	1	0.1%
19.45372487	1	0.1%
19.43975028	1	0.1%
19.26304537	1	0.1%
19.0777724	1	0.1%
19.0298245	1	0.1%
19.0213913	1	0.1%
18.99788436	1	0.1%

GitHub Forks (Log Scale)
Real number (ℝ)

MISSING ZEROS

Distinct	95
Distinct (%)	13.7%
Missing	426
Missing (%)	38.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.6360811

Minimum	0
Maximum	9.7377281
Zeros	165
Zeros (%)	14.7%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.69314718
median	1.3862944
Q3	2.4849066
95-th percentile	4.4693367
Maximum	9.7377281
Range	9.7377281
Interquartile range (IQR)	1.7917595

Descriptive statistics

Standard deviation	1.5244072
Coefficient of variation (CV)	0.93174307
Kurtosis	2.3333338
Mean	1.6360811
Median Absolute Deviation (MAD)	1.0116009
Skewness	1.2492479
Sum	1137.0764
Variance	2.3238174
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	165	14.7%
0.6931471806	107	9.5%
1.098612289	59	5.3%
1.386294361	44	3.9%
1.609437912	36	3.2%
1.791759469	25	2.2%
2.079441542	24	2.1%
1.945910149	20	1.8%
2.197224577	15	1.3%
2.564949357	14	1.2%
Other values (85)	186	16.6%
(Missing)	426	38.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	165	14.7%
0.6931471806	107	9.5%
1.098612289	59	5.3%
1.386294361	44	3.9%
1.609437912	36	3.2%
1.791759469	25	2.2%
1.945910149	20	1.8%
2.079441542	24	2.1%
2.197224577	15	1.3%
2.302585093	13	1.2%

Value	Count	Frequency (%)
9.737728084	1	0.1%
9.087607607	1	0.1%
8.051978079	1	0.1%
7.201170883	1	0.1%
7.109062136	1	0.1%
6.746412129	1	0.1%
6.29710932	1	0.1%
6.171700597	1	0.1%
6.169610732	1	0.1%
6.063785209	1	0.1%

GitHub Open Issues (Log Scale)
Real number (ℝ)

MISSING ZEROS

Distinct	76
Distinct (%)	16.7%
Missing	667
Missing (%)	59.5%
Infinite	0
Infinite (%)	0.0%
Mean	1.6723702

Minimum	0
Maximum	8.312626
Zeros	127
Zeros (%)	11.3%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1.3862944
Q3	2.7080502
95-th percentile	4.5544816
Maximum	8.312626
Range	8.312626
Interquartile range (IQR)	2.7080502

Descriptive statistics

Standard deviation	1.6104965
Coefficient of variation (CV)	0.96300238
Kurtosis	1.3000071
Mean	1.6723702
Median Absolute Deviation (MAD)	1.3862944
Skewness	1.0931026
Sum	759.25609
Variance	2.593699
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	127	11.3%
0.6931471806	52	4.6%
1.098612289	33	2.9%
1.386294361	31	2.8%
1.791759469	21	1.9%
1.945910149	16	1.4%
1.609437912	14	1.2%
2.079441542	12	1.1%
2.944438979	8	0.7%
2.302585093	8	0.7%
Other values (66)	132	11.8%
(Missing)	667	59.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	127	11.3%
0.6931471806	52	4.6%
1.098612289	33	2.9%
1.386294361	31	2.8%
1.609437912	14	1.2%
1.791759469	21	1.9%
1.945910149	16	1.4%
2.079441542	12	1.1%
2.197224577	7	0.6%
2.302585093	8	0.7%

Value	Count	Frequency (%)
8.312626026	1	0.1%
8.193400232	1	0.1%
7.691200098	1	0.1%
6.951772164	1	0.1%
6.825460036	1	0.1%
6.588926478	1	0.1%
6.29156914	1	0.1%
6.075346031	1	0.1%
5.926926026	1	0.1%
5.736572297	1	0.1%

Primary language
Categorical

Distinct	33
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

R	421
Python	220
Jupyter Notebook	195
HTML	117
MATLAB	50
Other values (28)	118

Length

Max length	24
Median length	17
Mean length	5.5976806
Min length	1

Characters and Unicode

Total characters	6275
Distinct characters	48
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	14 ?
Unique (%)	1.2%

Sample

1st row	Python
2nd row	Python
3rd row	C++
4th row	C++
5th row	Java

Common Values

Value	Count	Frequency (%)
R	421	37.6%
Python	220	19.6%
Jupyter Notebook	195	17.4%
HTML	117	10.4%
MATLAB	50	4.5%
Shell	16	1.4%
Java	15	1.3%
C++	15	1.3%
JavaScript	9	0.8%
Julia	9	0.8%
Other values (23)	54	4.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
r	421	31.7%
python	220	16.6%
jupyter	195	14.7%
notebook	195	14.7%
html	117	8.8%
matlab	50	3.8%
c	22	1.7%
shell	16	1.2%
java	15	1.1%
julia	9	0.7%
Other values (29)	66	5.0%

Most occurring characters

Value	Count	Frequency (%)
o	831	13.2%
t	635	10.1%
e	439	7.0%
R	425	6.8%
y	416	6.6%
h	237	3.8%
J	232	3.7%
n	229	3.6%
P	228	3.6%
r	220	3.5%
Other values (38)	2383	38.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4073	64.9%
Uppercase Letter	1966	31.3%
Space Separator	205	3.3%
Math Symbol	30	0.5%
Other Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	831	20.4%
t	635	15.6%
e	439	10.8%
y	416	10.2%
h	237	5.8%
n	229	5.6%
r	220	5.4%
u	212	5.2%
p	208	5.1%
k	200	4.9%
Other values (13)	446	11.0%

Uppercase Letter

Value	Count	Frequency (%)
R	425	21.6%
J	232	11.8%
P	228	11.6%
N	202	10.3%
T	175	8.9%
M	171	8.7%
L	170	8.6%
H	118	6.0%
A	102	5.2%
B	52	2.6%
Other values (12)	91	4.6%

Space Separator

Value	Count	Frequency (%)
	205	100.0%

Math Symbol

Value	Count	Frequency (%)
+	30	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6039	96.2%
Common	236	3.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	831	13.8%
t	635	10.5%
e	439	7.3%
R	425	7.0%
y	416	6.9%
h	237	3.9%
J	232	3.8%
n	229	3.8%
P	228	3.8%
r	220	3.6%
Other values (35)	2147	35.6%

Common

Value	Count	Frequency (%)
	205	86.9%
+	30	12.7%
.	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6275	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	831	13.2%
t	635	10.1%
e	439	7.0%
R	425	6.8%
y	416	6.6%
h	237	3.8%
J	232	3.7%
n	229	3.6%
P	228	3.6%
r	220	3.5%
Other values (38)	2383	38.0%

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	Project Name	GitHub Repository ID	Project Homepage	Project Repo URL	Project Landscape Category	GitHub Stars	GitHub Forks	GitHub Subscribers	GitHub Open Issues	GitHub Contributors	GitHub License Type	GitHub Description	GitHub Topics	GitHub Organization	GitHub Network Count	GitHub Detected Languages	Date Created	Date Most Recent Commit	Duration Created to Most Recent Commit	Duration Created to Now	Duration Most Recent Commit to Now	Repository Size (KB)	GitHub Repo Archived	Duration Created to Now in Years	Negative Duration Most Recent Commit to Now	category	GitHub Stars (Log Scale)	total lines of GitHub detected code	total lines of GitHub detected code (Log Scale)	GitHub Forks (Log Scale)	GitHub Open Issues (Log Scale)	Primary language
0	pandas	858127	https://pandas.pydata.org	https://github.com/pandas-dev/pandas	[cytomining-ecosystem-relevant-open-source]	40456	16945	1122	3617	412	BSD-3-Clause	Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more	[alignment, data-analysis, data-science, flexible, pandas, python]	pandas-dev	16945	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 364354.0, 'C#': None, 'C++': None, 'CMake': None, 'CSS': 6804.0, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': 1293498.0, 'D': None, 'Dockerfile': 5751.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': 457000.0, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': 10725.0, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 20699228.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 14470.0, 'Singularity': None, 'Smarty': 8486.0, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': 1196.0, 'eC': None, 'sed': None}	2010-08-24 01:37:33+00:00	2023-11-28 23:22:02+00:00	4844 days 21:44:29	4844 days 22:04:06.388583	0 days 00:19:37.388583	340201	False	13.271233	-1 days +23:40:22.611417	relevant-open-source	10.607970	22861512.0	16.944965	9.737728	8.193400	Python
1	numpy	908607	https://numpy.org	https://github.com/numpy/numpy	[cytomining-ecosystem-relevant-open-source]	25080	8845	596	2189	433	BSD-3-Clause	The fundamental package for scientific computing with Python.	[numpy, python]	numpy	8845	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 6225307.0, 'C#': None, 'C++': 271324.0, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': 164926.0, 'D': 19.0, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': 3787.0, 'Fortran': 29720.0, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 1697.0, 'Mako': None, 'Mercury': None, 'Meson': 89262.0, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 10542479.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 16810.0, 'Singularity': None, 'Smarty': 4129.0, 'Stan': None, 'Standard ML': None, 'Starlark': 1842.0, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': 5699.0}	2010-09-13 23:02:39+00:00	2023-11-28 21:57:52+00:00	4823 days 22:55:13	4824 days 00:39:00.388583	0 days 01:43:47.388583	135491	False	13.216438	-1 days +22:16:12.611417	relevant-open-source	10.129826	17357001.0	16.669506	9.087608	7.691200	Python
2	duckdb	138754790	http://www.duckdb.org	https://github.com/duckdb/duckdb	[cytomining-ecosystem-relevant-open-source]	13165	1223	159	280	260	MIT	DuckDB is an in-process SQL OLAP Database Management System	[analytics, database, embedded-database, olap, sql]	duckdb	1223	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 1768888.0, 'C#': None, 'C++': 34065812.0, 'CMake': 148295.0, 'CSS': 182.0, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': 388945.0, 'JavaScript': 12990.0, 'Jinja': None, 'Julia': 250843.0, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 15115.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 1472723.0, 'QMake': None, 'R': 1693.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 28867.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': 282550.0, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-06-26 15:04:45+00:00	2023-11-28 23:19:11+00:00	1981 days 08:14:26	1981 days 08:36:54.388583	0 days 00:22:28.388583	228261	False	5.427397	-1 days +23:37:31.611417	relevant-open-source	9.485317	38436903.0	17.464529	7.109062	5.634790	C++
3	arrow	51905353	https://arrow.apache.org/	https://github.com/apache/arrow	[cytomining-ecosystem-relevant-open-source]	12804	3140	351	4075	370	Apache-2.0	Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing	[arrow]	apache	3140	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': 3709.0, 'Batchfile': 32824.0, 'C': 1508127.0, 'C#': 1583808.0, 'C++': 27374565.0, 'CMake': 736400.0, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': 1728074.0, 'D': None, 'Dockerfile': 139128.0, 'Emacs Lisp': 1064.0, 'Forth': None, 'Fortran': None, 'FreeMarker': 2312.0, 'Gnuplot': None, 'Go': 5777080.0, 'Groovy': None, 'HCL': None, 'HTML': 5604.0, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': 7617061.0, 'JavaScript': 137865.0, 'Jinja': 22021.0, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': 8771.0, 'M': None, 'M4': None, 'MATLAB': 854595.0, 'Makefile': 32659.0, 'Mako': None, 'Mercury': None, 'Meson': 62865.0, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': 11472.0, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 3325524.0, 'QMake': None, 'R': 1703633.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': 1793463.0, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 415249.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': 680567.0, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': 39093.0, 'TypeScript': 1099743.0, 'VBA': None, 'VBScript': None, 'Vala': 24798.0, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': 1256.0}	2016-02-17 08:00:23+00:00	2023-11-28 23:41:36+00:00	2841 days 15:41:13	2841 days 15:41:16.388583	0 days 00:00:03.388583	174923	False	7.783562	-1 days +23:59:56.611417	relevant-open-source	9.457513	56723330.0	17.853696	8.051978	8.312626	C++
4	parquet-mr	20675636		https://github.com/apache/parquet-mr	[cytomining-ecosystem-relevant-open-source]	2230	1341	95	137	192	Apache-2.0	Apache Parquet	[big-data, java, parquet]	apache	1341	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': 6048043.0, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 14771.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': 8436.0, 'Scheme': None, 'Scilab': None, 'Shell': 14860.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': 10354.0, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2014-06-10 07:00:07+00:00	2023-11-28 23:31:50+00:00	3458 days 16:31:43	3458 days 16:41:32.388583	0 days 00:09:49.388583	18489	False	9.473973	-1 days +23:50:10.611417	relevant-open-source	7.709757	6096464.0	15.623219	7.201171	4.919981	Java
5	snakemake	212840200	https://snakemake.readthedocs.io	https://github.com/snakemake/snakemake	[cytomining-ecosystem-relevant-open-source]	1990	479	22	921	282	MIT	This is the development home of the workflow management system Snakemake. For general information, see	[reproducibility, snakemake, workflow-management]	snakemake	479	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 1346.0, 'C#': None, 'C++': None, 'CMake': None, 'CSS': 3033.0, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': 1727.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': 3647966.0, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': 43973.0, 'Jinja': 6950.0, 'Julia': 334.0, 'Jupyter Notebook': 4389.0, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 4400.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': 5.0, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 1339938.0, 'QMake': None, 'R': 786.0, 'Raku': None, 'Reason': None, 'Rebol': 6.0, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': 6.0, 'Ruby': None, 'Rust': 3617.0, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 5149.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': 5722.0, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2019-10-04 14:58:11+00:00	2023-11-28 15:33:22+00:00	1516 days 00:35:11	1516 days 08:43:28.388583	0 days 08:08:17.388583	91664	False	4.153425	-1 days +15:51:42.611417	relevant-open-source	7.595890	5069347.0	15.438723	6.171701	6.825460	HTML
6	seurat	35927665	http://www.satijalab.org/seurat	https://github.com/satijalab/seurat	[cytomining-ecosystem-adjacent-tools]	1987	851	79	282	88	NOASSERTION	R toolkit for single cell genomics	[cran, human-cell-atlas, single-cell-genomics, single-cell-rna-seq]	satijalab	851	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 166.0, 'C#': None, 'C++': 103885.0, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': 1528326.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 942.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2015-05-20 05:23:02+00:00	2023-11-28 20:43:37+00:00	3114 days 15:20:35	3114 days 18:18:37.388583	0 days 02:58:02.388583	22924	False	8.531507	-1 days +21:01:57.611417	adjacent-tools	7.594381	1633319.0	14.306125	6.746412	5.641907	R
7	napari	144513571	https://napari.org	https://github.com/napari/napari	[microscopy-analysis-tools]	1953	394	49	1045	149	BSD-3-Clause	napari: a fast, interactive, multi-dimensional image viewer for python	[napari, numpy, python, visualization]	napari	394	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': 465.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 6722.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 4689846.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': 2846.0, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 1221.0, 'Singularity': 95.0, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-08-13 01:12:28+00:00	2023-11-28 23:41:39+00:00	1933 days 22:29:11	1933 days 22:29:11.388583	0 days 00:00:00.388583	77793	False	5.295890	-1 days +23:59:59.611417	microscopy-analysis-tools	7.577122	4701195.0	15.363327	5.976351	6.951772	Python
8	scanpy	80342493	https://scanpy.readthedocs.io	https://github.com/scverse/scanpy	[cytomining-ecosystem-adjacent-tools]	1645	543	52	540	128	BSD-3-Clause	Single-cell analysis in Python. Scales to >1M cells.	[anndata, bioinformatics, data-science, machine-learning, python, scanpy, scverse, transcriptomics, visualize-data]	scverse	543	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 1331726.0, 'QMake': None, 'R': 2315.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2017-01-29 11:31:11+00:00	2023-11-28 17:59:42+00:00	2494 days 06:28:31	2494 days 12:10:28.388583	0 days 05:41:57.388583	38584	False	6.832877	-1 days +18:18:02.611417	adjacent-tools	7.405496	1334041.0	14.103723	6.297109	6.291569	Python
9	STAR	17778869		https://github.com/alexdobin/STAR	[cytomining-ecosystem-adjacent-tools]	1623	478	87	727	34	MIT	RNA-seq aligner	[]	None	478	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': 24345.0, 'Batchfile': None, 'C': 2350683.0, 'C#': None, 'C++': 1210764.0, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': 676.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 1006.0, 'Makefile': 25383.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': 11364.0, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 295.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': 119547.0, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2014-03-15 15:47:05+00:00	2023-09-08 12:23:35+00:00	3463 days 20:36:30	3545 days 07:54:34.388583	81 days 11:18:04.388583	541229	False	9.712329	-82 days +12:41:55.611417	adjacent-tools	7.392032	3744063.0	15.135682	6.169611	6.588926	C

	Project Name	GitHub Repository ID	Project Homepage	Project Repo URL	Project Landscape Category	GitHub Subscribers	GitHub Contributors	GitHub License Type	GitHub Description	GitHub Topics	GitHub Organization	GitHub Detected Languages	Date Created	Date Most Recent Commit	Duration Created to Most Recent Commit	Duration Created to Now	Duration Most Recent Commit to Now	Repository Size (KB)	GitHub Repo Archived	Duration Created to Now in Years	Negative Duration Most Recent Commit to Now	category	GitHub Stars (Log Scale)	total lines of GitHub detected code	total lines of GitHub detected code (Log Scale)	GitHub Forks (Log Scale)	GitHub Open Issues (Log Scale)	Primary language
1111	BloodVesselImageAnalysis	323621577		https://github.com/RoopaMadhu/BloodVesselImageAnalysis	[related-tools-github-query-result]	1	1	None	Spatiographic projections of biological systems	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 188297.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-12-22 12:36:17+00:00	2020-12-22 14:22:59+00:00	0 days 01:46:42	1071 days 11:05:22.388583	1071 days 09:18:40.388583	576	False	2.934247	-1072 days +14:41:19.611417	github-query-result	NaN	188297.0	12.145776	NaN	NaN	MATLAB
1112	SickleCellDataAnalysis	298584969	None	https://github.com/ridz46/SickleCellDataAnalysis	[related-tools-github-query-result]	1	1	None	This repository contains the codes used for image processing and further downstream data analysis for the project on the development of a point-of-care diagnostic test for sickle cell disease. This repository is maintained by the Microfluidics & Biological Physics group, Department of Biosciences & Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': 4373.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-09-25 13:45:27+00:00	2020-09-28 08:55:24+00:00	2 days 19:09:57	1159 days 09:56:12.388583	1156 days 14:46:15.388583	17	False	3.175342	-1157 days +09:13:44.611417	github-query-result	NaN	4373.0	8.383205	NaN	NaN	R
1113	Data-Analysis-AMATH-482	245942374	None	https://github.com/priyanshir/Data-Analysis-AMATH-482	[related-tools-github-query-result]	1	1	None	Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences. Brief review of statistical methods and their computational implementation for studying time series analysis, spectral analysis, filtering methods, principal component analysis, orthogonal mode decomposition, and image processing and compression	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': 703573.0, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 33375.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-03-09 04:17:02+00:00	2020-03-14 22:41:50+00:00	5 days 18:24:48	1359 days 19:24:37.388583	1354 days 00:59:49.388583	2832	False	3.723288	-1355 days +23:00:10.611417	github-query-result	NaN	736948.0	13.510273	NaN	NaN	Jupyter Notebook
1114	Aging-Cell-Morphology-Cell-transformations-and-image-processing	235024426	None	https://github.com/sumisingh/Aging-Cell-Morphology-Cell-transformations-and-image-processing	[related-tools-github-query-result]	1	1	None	Identifying cellular transformations associated with aging using image processing	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': 8130261.0, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-01-20 05:18:57+00:00	2020-01-20 05:29:56+00:00	0 days 00:10:59	1408 days 18:22:42.388583	1408 days 18:11:43.388583	27874	False	3.857534	-1409 days +05:48:16.611417	github-query-result	NaN	8130261.0	15.911104	NaN	NaN	Jupyter Notebook
1115	Cell-virulence-Detection-using-Image-Processing	163268436	None	https://github.com/arushigupta148/Cell-virulence-Detection-using-Image-Processing	[related-tools-github-query-result]	1	1	None	Designed an automated tool to find the thickness of multiple cell capsules from images using morphological operations to generate plots of cell size vs capsular thickness, simplifying detection of virulence in yeast cells for mycologists	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 12989.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-12-27 08:27:06+00:00	2019-05-12 23:09:02+00:00	136 days 14:41:56	1797 days 15:14:33.388583	1661 days 00:32:37.388583	1751	False	4.923288	-1662 days +23:27:22.611417	github-query-result	NaN	12989.0	9.471858	NaN	NaN	Python
1116	CellMorphology	148259959		https://github.com/KnightofDawn/CellMorphology	[related-tools-github-query-result]	1	1	None	Python code to identify/analyze cells from microscopic stack images.	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 65906.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-09-11 04:25:09+00:00	2018-09-10 20:41:28+00:00	-1 days +16:16:19	1904 days 19:16:30.388583	1905 days 03:00:11.388583	161	False	5.216438	-1906 days +20:59:48.611417	github-query-result	NaN	65906.0	11.095985	NaN	NaN	Python
1117	ImagingCells	137526283	None	https://github.com/jesnyder/ImagingCells	[related-tools-github-query-result]	1	1	None	Scripts to analyze cell number and morphologies using images.	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': 1523.0, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-06-15 19:50:00+00:00	2018-08-31 19:21:33+00:00	76 days 23:31:33	1992 days 03:51:39.388583	1915 days 04:20:06.388583	1	False	5.457534	-1916 days +19:39:53.611417	github-query-result	NaN	1523.0	7.328437	NaN	NaN	Jupyter Notebook
1118	course-bia	119301640	None	https://github.com/denzf/course-bia	[related-tools-github-query-result]	1	1	MIT	Code examples for the course of Biological Image Analysis	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 6010.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-01-28 21:58:13+00:00	2018-01-24 03:22:19+00:00	-5 days +05:24:06	2130 days 01:43:26.388583	2134 days 20:19:20.388583	203	False	5.835616	-2135 days +03:40:39.611417	github-query-result	NaN	6010.0	8.701180	NaN	NaN	Python
1119	Image-analysis	152904377		https://github.com/dguin/Image-analysis	[related-tools-github-query-result]	0	1	None	The repository contains code to analyze videos where each frame is a snapshot of the cellular status as a function of time. The program includes subroutines for segmentation protocols to pick a cell and differentiate it from the background when the signal to noise is low. The protocol docx explains what each code does and explains the order in which they must be run. As is the program analyzes FRET data from a cell, where the temperature increases as a function of time and one can evaluate the changes in the cell morphology as the cell is under heat stress	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 40670.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-10-13 18:53:42+00:00	2018-10-13 19:32:22+00:00	0 days 00:38:40	1872 days 04:47:57.388583	1872 days 04:09:17.388583	26	False	5.128767	-1873 days +19:50:42.611417	github-query-result	NaN	40670.0	10.613246	NaN	NaN	MATLAB
1120	oct-image-analysis	125785309		https://github.com/ricster101/oct-image-analysis	[related-tools-github-query-result]	0	1	None	Work developed with Adriana Costa during the course of Computer Vision and Biological Perception aiming to discover differences in mice retina	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Inno Setup': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Limbo': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 22755.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBA': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-03-19 01:29:32+00:00	2018-03-19 03:31:25+00:00	0 days 02:01:53	2080 days 22:12:07.388583	2080 days 20:10:14.388583	16	False	5.698630	-2081 days +03:49:45.611417	github-query-result	NaN	22755.0	10.032540	NaN	NaN	MATLAB

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