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@conormm
conormm / r-to-python-data-wrangling-basics.md
Last active May 3, 2025 19:21
R to Python: Data wrangling with dplyr and pandas

R to python data wrangling snippets

The dplyr package in R makes data wrangling significantly easier. The beauty of dplyr is that, by design, the options available are limited. Specifically, a set of key verbs form the core of the package. Using these verbs you can solve a wide range of data problems effectively in a shorter timeframe. Whilse transitioning to Python I have greatly missed the ease with which I can think through and solve problems using dplyr in R. The purpose of this document is to demonstrate how to execute the key dplyr verbs when manipulating data using Python (with the pandas package).

dplyr is organised around six key verbs:

@ryanpraski
ryanpraski / google_analytics_api_v3_10krows_nosampling_multiple_profiles_ryanpraski.py
Last active February 1, 2024 13:44
A solution for exporting more than 10,000 rows and a solution for the sampling limitations of Google Analytics using Python and the Google Analytics API. Includes functionality to pull data from multiple Google Analytics profiles.
#!/usr/bin/python
# -*- coding: utf-8 -*-
#
# Copyright 2012 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
---
title: "Introduction to dplyr"
author: "mz"
date: "09/21/2014"
output:
html_document:
keep_md: yes
---
```{r imports,echo=FALSE, warning=FALSE, error=FALSE, message=FALSE}