• Pandas Basics Cheat Sheet (2021) Python For Data Science
• Pandas Data Science Cheat Sheet
• Pandas Basics Cheat Sheet Pdf

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

• Series
• DataFrames
  • Slicing and dicing DataFrames
  • Conditional selection
  • Operations on DataFrames
  • DataFrame index

Series¶¶

With pandas Cheat Sheet Syntax –Creating DataFrames Tidy Data –A foundation for wrangling in pandas In a tidy data set: F M A Each variable is saved in its own column & Each observation is saved in its own row Tidy data complements pandas’svectorized operations. Pandas will automatically preserve. Pandas Cheat Sheet: top 35 commands and operations Pandas is one of the most popular tools for data analysis in Python. This open-source library is the backbone of many data projects and is used for data cleaning and data manipulation. With Pandas, you gain greater control over complex data sets.

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¶¶

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.

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]]

Conditional selection¶¶

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

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 &, |

Pandas Basics Cheat Sheet (2021) Python For Data Science

Operations on DataFrames¶¶

Adding new columns¶¶

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

Dropping rows and columns¶¶

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

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

Pandas Data Science Cheat Sheet

Set index¶¶

Pandas Basics Cheat Sheet Pdf