Numpy, Pandas, And Matplotlib Cheat Sheet Numpy Pandas Reference Guide

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Numpy and Pandas Cheat Sheet

Common Imports

import numpy as np

import pandas ps pd

import matplotlib.pyplot as plt

import seaborn as sns

Vectorized Operations

xs + ys ........................Element-wise addition

xs + z ............................... Adding a scalar

xs & ys ........................Bitwise (boolean) and

xs | ys ..........................bitwise (boolean) or

xs .............................Bitwise (boolean) not

xs < ys .................................... Less than

Subtraction (-), multiplication (*), division (/), expo-

nentiation (**), and other comparison operators (<=,

>,>=, ==, !=) work similarly.

matplotlib plotting

plt.hist(xs)..............................Histogram

plt.scatter(xs, ys).....................Scatterplot

plt.plot(xs, ys) ..........................Line plot

Array / Series functions

max() ......................................Maximum

min() ......................................Minumum

mean()................................Mean (average)

median() .....................................Median

sum().....................................Sum (total)

Accessing Data in a Series

s.iloc[i]....................Get element by position

s.loc[x] ....................... Get element by index

s.values ...........................Get NumPy array

Plotting for Series

s.hist() .................................. Histogram

s.plot()....................................Line plot

Apply Functions

s.apply(value -> value) ........... returns a Series

df.applymap(value -> value) .returns a DataFrame

df.apply(series -> value) .........returns a Series

df.apply(series -> series). . . returns a DataFrame

Accessing Data in a DataFrame

df[’col’] .......................Get column by name

df.iloc[i] ...................... Get row by position

df.loc[x] ..........................Get row by index

df.iloc[i, j] ...............Get element by position

df.loc[x, y]...................Get element by index

df.values ......................Get 2D NumPy array

DataFrame Summarization

df.describe() ..............Stats about each column

df.head(n) ..............................First n rows

df.tail(n)...............................Last n rows

df.columns .....................List of column names

Axis Argument

df.mean(axis=0) ............... mean of each column

df.mean(axis=1) ...................mean of each row

df.mean(axis=’index’) ........ mean of each column

df.mean(axis=’columns’ ...........................)

mean of each row

Plotting for DataFrames

df.plot() .........Line plot with one line per column