Pandas Cheat Sheet

Posted : admin On 1/29/2022

Pandas cheat sheet¶¶

PYTHON PANDAS Cheat Sheet by sanjeev95 - Cheatography.com Created Date: 0656Z. Python For Data Science Cheat Sheet Pandas Basics Learn Python for Data Science Interactively at www.DataCamp.com Pandas DataCamp Learn Python for Data Science Interactively Series DataFrame 4 Index 7-5 3 d c b A one-dimensional labeled array a capable of holding any data type Index Columns A two-dimensional labeled data structure with columns.

Pandas Cheat Sheet

Pandas is Python Data Analysis library. Series and Dataframes are major data structures in Pandas. Pandas is built on top of NumPy arrays.

ToC

Pandas cheat sheet dataquest
  • Series
  • DataFrames
    • Slicing and dicing DataFrames
    • Conditional selection
    • Operations on DataFrames
    • DataFrame index

Series¶¶

Series is 1 dimensional data structure. It is similar to numpy array, but each data point has a label in the place of an index.

Create a series¶¶

Pandas

Thus Series can have different datatypes.

Operations on series¶¶

You can add, multiply and other numerical opertions on Series just like on numpy arrays.

When labels dont match, it puts a nan. Thus when two series are added, you may or may not get the same number of elements

DataFrames¶¶

Creating dataFrames¶¶

Pandas DataFrames are built on top of Series. It looks similar to a NumPy array, but has labels for both columns and rows.

reliabilitycostcompetitionhalflife
Car10.1343020.6252070.9709810.717605
Car20.7137660.7731820.0596890.450899
Car30.0589900.9043010.4314870.087683
Car40.5098910.5010370.2442790.763135

Slicing and dicing DataFrames¶¶

You can access DataFrames similar to Series and slice it similar to NumPy arrays

Access columns¶¶
Accessing using index number¶¶

If you don’t know the labels, but know the index like in an array, use iloc and pass the index number.

Dicing DataFrames¶¶

Dicing using labels > use DataFrameObj.loc[[row_labels],[col_labels]]

costcompetition
Car20.9353680.719570
Car30.6599500.605077
costcompetition
Car20.9353680.719570
Car30.6599500.605077

Conditional selection¶¶

When running a condition on a DataFrame, you are returned a Bool dataframe.

reliabilitycostcompetitionhalflife
Car10.7764150.4350830.2361510.169087
Car20.7904030.9874590.3705700.734146
Car30.8847830.2338030.6916390.725398
Car40.6930380.7168240.7669370.490821
reliabilitycostcompetitionhalflife
Car30.8847830.2338030.6916390.725398
Chaining conditions¶¶

In a Pythonic way, you can chain conditions

Multiple conditions¶¶

You can select dataframe elements with multiple conditions. Note cannot use Python and , or. Instead use &,

reliabilitycostcompetitionhalflife
Car10.7764150.4350830.2361510.169087
Car20.7904030.9874590.3705700.734146
Pandas cheat sheet dataquest
reliabilitycostcompetitionhalflife
Car10.7764150.4350830.2361510.169087
Car20.7904030.9874590.3705700.734146
Car30.8847830.2338030.6916390.725398

Operations on DataFrames¶¶

Adding new columns¶¶

Create new columns just like adding a kvp to a dictionary.

reliabilitycostcompetitionhalflifefull_life
Car10.1343020.6252070.9709810.7176051.435210
Car20.7137660.7731820.0596890.4508990.901799
Car30.0589900.9043010.4314870.0876830.175366
Car40.5098910.5010370.2442790.7631351.526270
Dropping rows and columns¶¶

Row labels are axis = 0 and columns are axis = 1

reliabilitycostcompetitionhalflife
Car10.1343020.6252070.9709810.717605
Car20.7137660.7731820.0596890.450899
Car30.0589900.9043010.4314870.087683
Car40.5098910.5010370.2442790.763135
reliabilitycostcompetitionhalflifefull_life
Car10.1343020.6252070.9709810.7176051.435210
Car20.7137660.7731820.0596890.4508990.901799
Car40.5098910.5010370.2442790.7631351.526270
reliabilitycostcompetitionhalflifefull_life
Car10.1343020.6252070.9709810.7176051.43521
Car40.5098910.5010370.2442790.7631351.52627

Python Pandas Documentation Pdf

DataFrame Index¶¶

So far, Car1, Car2.. is the index for rows. If you would like to set a different column as an index, use set_index. If you want to make index as a column rather, and use numerals for index, use reset_index

Set index¶¶
reliabilitycostcompetitionhalflifecar_names
Car10.7764150.4350830.2361510.169087altima
Car20.7904030.9874590.3705700.734146outback
Car30.8847830.2338030.6916390.725398taurus
Car40.6930380.7168240.7669370.490821mustang

Pandas Cheat Sheet For Data Analysis

reliabilitycostcompetitionhalflifecar_names
car_names
altima0.7764150.4350830.2361510.169087altima
outback0.7904030.9874590.3705700.734146outback
taurus0.8847830.2338030.6916390.725398taurus
mustang0.6930380.7168240.7669370.490821mustang

Pandas Cheat Sheet Pdf

indexreliabilitycostcompetitionhalflifecar_names
0Car10.7764150.4350830.2361510.169087altima
1Car20.7904030.9874590.3705700.734146outback
2Car30.8847830.2338030.6916390.725398taurus
3Car40.6930380.7168240.7669370.490821mustang