Datasets:
dnanper
/
dscoder_lib_usage_2

Dataset card Data Studio Files
xet
 Community
1
usage_count
int64
1
15.9k
rank
int64
1
146
percentage_of_total
float64
0
38.5
examples_count
int64
1
15.9k
name
stringlengths
2
22
15,892
1
38.524193
15,892
tensorflow
12,410
2
30.08339
12,410
sklearn
4,458
3
10.806749
4,458
pandas
2,607
4
6.319694
2,607
matplotlib
2,542
5
6.162125
2,542
numpy
1,319
6
3.197421
1,319
torch
486
7
1.178125
486
nltk
95
8
0.230292
95
flask
62
9
0.150296
62
re
60
10
0.145447
60
os
58
11
0.140599
58
transformers
57
12
0.138175
57
requests
55
13
0.133327
55
tkinter
52
14
0.126054
52
torchvision
50
15
0.121206
50
random
49
16
0.118782
49
gym
49
17
0.118782
49
plotly
41
18
0.099389
41
tflearn
34
19
0.08242
34
json
31
20
0.075148
31
scipy
31
21
0.075148
31
collections
30
22
0.072724
30
seaborn
29
23
0.0703
29
streamlit
28
24
0.067875
28
xgboost
27
25
0.065451
27
tweepy
24
26
0.058179
24
torchtext
24
27
0.058179
24
bs4
23
28
0.055755
23
datetime
20
29
0.048482
20
librosa
20
30
0.048482
20
string
19
31
0.046058
19
http
18
32
0.043634
18
gensim
17
33
0.04121
17
deap
16
34
0.038786
16
argparse
15
35
0.036362
15
pickle
14
36
0.033938
14
socketserver
14
37
0.033938
14
tensorflow_hub
14
38
0.033938
14
mpl_toolkits
14
39
0.033938
14
skopt
13
40
0.031514
13
sqlite3
12
41
0.029089
12
spacy
12
42
0.029089
12
statsmodels
11
43
0.026665
11
sys
11
44
0.026665
11
cv2
10
45
0.024241
10
wordcloud
10
46
0.024241
10
phoebe
10
47
0.024241
10
networkx
10
48
0.024241
10
google
10
49
0.024241
10
math
10
50
0.024241
10
psycopg2
9
51
0.021817
9
time
9
52
0.021817
9
textblob
9
53
0.021817
9
pyautogui
9
54
0.021817
9
mido
9
55
0.021817
9
imblearn
8
56
0.019393
8
thriftpy
8
57
0.019393
8
Utils
8
58
0.019393
8
bokeh
8
59
0.019393
8
pyemma
7
60
0.016969
7
tensorflow_datasets
7
61
0.016969
7
io
7
62
0.016969
7
skimage
7
63
0.016969
7
qrcode
6
64
0.014545
6
pandas_datareader
6
65
0.014545
6
selenium
6
66
0.014545
6
tolt
6
67
0.014545
6
PIL
6
68
0.014545
6
simpleml
6
69
0.014545
6
dialogflow_v2
5
70
0.012121
5
graphviz
5
71
0.012121
5
inpututils
5
72
0.012121
5
autokeras
5
73
0.012121
5
describe
5
74
0.012121
5
joblib
5
75
0.012121
5
smtplib
5
76
0.012121
5
surprise
5
77
0.012121
5
tensorflow_addons
5
78
0.012121
5
mlxtend
4
79
0.009696
4
pymongo
4
80
0.009696
4
email
4
81
0.009696
4
gpt_2_simple
4
82
0.009696
4
stable_baselines
4
83
0.009696
4
rasa_nlu
4
84
0.009696
4
speech_recognition
4
85
0.009696
4
boto3
4
86
0.009696
4
django
4
87
0.009696
4
kerastuner
4
88
0.009696
4
PyPDF2
3
89
0.007272
3
yfinance
3
90
0.007272
3
pyodbc
3
91
0.007272
3
RForest
3
92
0.007272
3
mpi4py
3
93
0.007272
3
pycas
3
94
0.007272
3
dash
3
95
0.007272
3
bayes_opt
3
96
0.007272
3
sklearn_crfsuite
3
97
0.007272
3
flask_restful
3
98
0.007272
3
sqlalchemy
3
99
0.007272
3
evolutionary_search
2
100
0.004848
2
ga