📊 Python Data Science Snippets

Python Data Science Snippets is a collection of Sublime Text snippets for data science and machine learning in Python.

💻 Installation

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!

📈 Snippets

• Imports
• NumPy
• Pandas
• Matplotlib
• Scikit-learn
• Keras
• PyTorch

Imports

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

NumPy

Trigger	Description
arange	np.arange
array	np.array
linspace	np.linspace
logspace	np.logspace
ones	np.ones
zeros	np.zeros

Pandas

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

Matplotlib

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

Scikit-learn

Trigger	Description
knn	KNeighborsClassifier
linreg	LinearRegression
logreg	LogisticRegression
rfc	RandomForestClassifier
tts	train_test_split

Keras

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

PyTorch

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.