Pandas

Read a CSV file into a DataFrame

View the first few rows of a DataFrame

Get concise summary of DataFrame

Generate descriptive statistics of numeric columns

Select rows and columns by labels

Select rows and columns by integer position

Group DataFrame using one or more columns

Combine DataFrames using database-style joins

Create a pivot table from DataFrame

Remove rows or columns with missing values

Fill NaN values with a specified value

Sort rows by values or index

Concatenate DataFrames along rows or columns

Save DataFrame to a CSV file

Save DataFrame to an Excel file

Convert column to datetime format

Access datetime properties like year, month, day

Plot DataFrame or Series

Unpivot DataFrame from wide to long format

Reshape data from long to wide format

Vectorized string methods for Series

Convert column to categorical dtype

Convert Series to specified dtype

Find unique values in a Series

Count occurrences of each unique value

Perform rolling window calculations

Calculate expanding statistics

Check DataFrame memory usage