Pandas Basic Snippets installs statistics

Snippington Python Pandas Basic

Visual Studio Code extension for Pandas code snippets.

This works with ipynb (Jupyter Notebook) files in Visual Studio Code too.

Notice: Starting from version 0.1.8, AI and GPT platforms will be used to generate new shortcuts and snippets.

Data Exploratory Shortcuts

Prefix	Description
pd: imp	Import Pandas
pd: read-csv	Read CSV File
pd: read-csv-chunked	Read CSV File in Chunks
pd: read-csv-skiprows	Read CSV with skipping rows
pd: stats	Show aggregate stats.
pd: stats-custom	Get Custom Aggregate Stats
pd: shape	Get the shape of dataframe
pd: row-count	Get the row count of dataframe
pd: column-count	Get the column count of dataframe
pd: first-x-rows	Get the first x rows of dataframe
pd: last-x-rows	Get the last x rows of dataframe
pd: n-largest	Get the n largest values of a column in a dataframe.
pd: n-smallest	Get the n smallest values of a column in a dataframe.
pd: set-categories	Define categories
pd: frequency-distribution	Get frequency distribution of values for a column
pd: data-sample	Get sample of data from dataframe
pd: column-select	Select single column from dataframe
pd: column-select-multiple	Select multiple columns from dataframe
pd: rows-specific-columns	Select rows by indices for specific column names in dataframe
pd: rows-by-index	Select rows from dataframe by indices
pd: columns-by-index	Select columns from dataframe by indices
pd: group-by-count	Group By with Count Aggregate
pd: group-by-mean	Group By with Mean
pd: window-expanding-mean	Expanding Window Mean
pd: window-rolling-mean	Expanding Window Mean

Data Manipulation Shortcuts

Prefix	Description
pd: dataframe-create	Create custom dataframe
pd: columns-rename	Assign new column names to dataframe
pd: columns-rename-specific	Assign new column names to specific columns in dataframe
pd: replace	Replace values a dataframe.
pd: columns-drop	Drop columns by name
pd: duplicates-drop	Drop duplicate columns by name
pd: sort-by-column	Sort values in dataframe by column
pd: filter	Filter dataframe based on condition/match
pd: filter-by-query	Filter dataframe by query based on conditions
pd: apply-all	Apply function to all of dataframe
pd: apply-single-column	Apply function to a specific column
pd: apply-multiple-columns	Apply function to multiple columns
pd: apply-column-lambda	Apply lambda function to column
pd: convert-numeric	Convert all columns to numeric type
pd: convert-column-numeric	Convert a single column to numeric type
pd: convert-columns-numeric	Convert multiple columns to numeric type
pd: set-data-types	Assign data types to columns
pd: dataframes-concatenate	Concatenate dataframes
pd: pivot-table	Create Pivot table

Time Series Operations

Prefix	Description
pd: parse-dates	Read CSV with date parsing
pd: resample	Resample time series data to a different frequency
pd: date-range	Create a date range with pandas
pd: filter-date-range	Filter dataframe by date range
pd: date-components	Extract date components from datetime column
pd: time-shift	Shift time series data by periods
pd: time-lag-features	Create multiple lag features for time series analysis
pd: time-diff	Calculate differences between consecutive periods
pd: time-pct-change	Calculate percentage change between consecutive periods
pd: set-datetime-index	Set a datetime column as index and sort

Missing Data Fix Shortcuts

Prefix	Description
pd: fill-mean	Fill missing values with mean values
pd: fill-median	Fill missing values with median values
pd: fill-mode	Fill missing values with modal values

Output Shortcuts

Prefix	Description
pd: write-to-excel	Write dataframe to Excel file
pd: write-to-csv	Write dataframe to CSV file

Plotting Shortcuts

Prefix	Description
pd: scatter-plot	Create a scatter Plot
pd: bar-plot	Create a bar plot
pd: line-plot-multiple	Create a multiple line plot
pd: plot-save	Save plot to output file
pd: bar-plot-horizontal	Horizontal bar plot
pd: histogram	Make a histogram
pd: histogram-columns	Make a histogram for each column

Pre-reqs

Make sure you have Python, Pandas and Matplotlib installed (optional: for plots only).

pip3 install pandas
pip3 install matplotlib