📊 Python Data Science Snippets
Python Data Science Snippets is a collection of Sublime Text snippets for data science and machine learning in Python.
The easiest way to install Python Data Science Snippets is through Package Control . After it is enabled inside Sublime Text, open the command palette and find Package Control: Install Package and press ENTER. Then, find Python Data Science Snippets in the list. Press ENTER again, and this package is installed!
Import snippets start with i followed by the package/module's import alias.
Trigger
Description
ikeras
from tensorflow import keras
inp
import numpy as np
ipd
import pandas as pd
iplt
import matplotlib.pyplot as plt
isklearn
from sklearn.$1 import $2
isns
import seaborn as sns
itf
import tensorflow as tf
itorch
import torch
inn
from torch import nn
idl
from torch.utils.data import DataLoader
Trigger
Description
arange
np.arange
array
np.array
linspace
np.linspace
logspace
np.logspace
ones
np.ones
zeros
np.zeros
Trigger
Description
apply
df.apply
columns
df.columns
describe
df.describe
df
pd.DataFrame
dropna
df.dropna
fillna
df.fillna
groupby
df.groupby
head
df.head
read_csv
pd.read_csv
rename
df.rename
reset_index
df.reset_index
sample
df.sample
ser
pd.Series
tail
df.tail
to_csv
df.to_csv
to_datetime
pd.to_datetime
Trigger
Description
annotate
plt.annotate
bar_label
plt.bar_label
bar
plt.bar
barh
plt.barh
fill_between
plt.fill_between
hist
plt.hist
imread
plt.imread
imsave
plt.imsave
imshow
plt.imshow
legend
plt.legend
pie
plt.pie
plot
plt.plot
savefig
plt.savefig
scatter
plt.scatter
show
plt.show
stackplot
plt.stackplot
subplot
plt.subplot
subplots
plt.subplots
suptitle
plt.suptitle
text
plt.text
tight_layout
plt.tight_layout
title
plt.title
xlabel
plt.xlabel
xlim
plt.xlim
ylabel
plt.ylabel
ylim
plt.ylim
Trigger
Description
knn
KNeighborsClassifier
linreg
LinearRegression
logreg
LogisticRegression
rfc
RandomForestClassifier
tts
train_test_split
Trigger
Description
compile
model.compile
evaluate
model.evaluate
fit
model.fit
layer
keras.layers.layer
load_model
keras.models.load_model
predict
model.predict
save
model.save
sequential
keras.Sequential
Trigger
Description
dataloader
torch.utils.data.DataLoader
device
torch.device (cuda/cpu)
module
torch.nn.Module
The snippet files are in the snippets folder of this GitHub repository .