Pandas — quick reference for the busy data scientist

( Pandas snippets that I find useful for day to day tasks )

I want this guide to be a no-nonsense and quick reference sheet to refresh your data munging skills in pandas. So let’s dive into pandas directly.

Note: You can play around with any dataset you like.

Quick Pandas Vocabulary:

dataframe: Two-dimensional structure of data similar to a spreadsheet

series: One-dimensional indexed array of fixed data type

First, let’s load pandas

import pandas as pd
url = “https://raw.githubusercontent.com/jokecamp/FootballData/master/Germany/Bundesliga/1964/matches.csv"

1. You can load data from the internet without downloading

data = pd.read_csv(url)
data.head()

reading data from url

(Note: tail() command picks rows from tail, also you can pass numerical parameters to head and tail commands)

Some of the exploratory data analysis(EDA) commands you can try with pandas:

# print column names
data.columns
# print general…