bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

dannguyen

Using the t and csvkit to quickly collect and analyze #nicar16 tweets from the command-line

The t command-line Twitter tool is a great way to work with Twitter information in a spreadsheet.

Its homepage with good installation instructions is here:

https://github.com/sferik/t

And I've written some related instructions about how to get an authentication token from Twitter:

zstumgoren

• Zen of Python (wherein all your questions are answered)

import this

• Hitchhiker's Guide to Python
• (Re)designing code
• PythonJournos Google Group

Your humble guides (ping us):

wjmazza

/*

This script is meant to be used with a Google Sheets spreadsheet. When you edit a cell containing a
valid CSS hexadecimal colour code (like #000 or #000000), the background colour will be changed to
that colour and the font colour will be changed to the inverse colour for readability.

To use this script in a Google Sheets spreadsheet:
1. go to Tools » Script Editor » Spreadsheet;
2. erase everything in the text editor;
3. change the title to "Set colour preview on edit";

shanealynn

# Single selections using iloc and DataFrame
# Rows:
data.iloc[0] # first row of data frame (Aleshia Tomkiewicz) - Note a Series data type output.
data.iloc[1] # second row of data frame (Evan Zigomalas)
data.iloc[-1] # last row of data frame (Mi Richan)
# Columns:
data.iloc[:,0] # first column of data frame (first_name)
data.iloc[:,1] # second column of data frame (last_name)
data.iloc[:,-1] # last column of data frame (id)

shanealynn

# Multiple row and column selections using iloc and DataFrame
data.iloc[0:5] # first five rows of dataframe
data.iloc[:, 0:2] # first two columns of data frame with all rows
data.iloc[[0,3,6,24], [0,5,6]] # 1st, 4th, 7th, 25th row + 1st 6th 7th columns.
data.iloc[0:5, 5:8] # first 5 rows and 5th, 6th, 7th columns of data frame (county -> phone1).

shanealynn

# Select rows with index values 'Andrade' and 'Veness', with all columns between 'city' and 'email'
data.loc[['Andrade', 'Veness'], 'city':'email']
# Select same rows, with just 'first_name', 'address' and 'city' columns
data.loc['Andrade':'Veness', ['first_name', 'address', 'city']]
 
# Change the index to be based on the 'id' column
data.set_index('id', inplace=True)
# select the row with 'id' = 487
data.loc[487]

vickyqian

import tweepy
import csv
import pandas as pd
####input your credentials here
consumer_key = ''
consumer_secret = ''
access_token = ''
access_token_secret = ''

auth = tweepy.OAuthHandler(consumer_key, consumer_secret)

zufanka

Contents

• SQL
• Python
  • lists
  • dicts
  • dates
• Pandas
• Selenium
• Numpy
• Altair

morisy

import requests
import csv
from documentcloud import DocumentCloud # https://documentcloud.readthedocs.io/en/latest/gettingstarted.html#installation

# Install DocumentCloud Python Wrapper first: https://documentcloud.readthedocs.io/en/latest/index.html

USERNAME = input('Username: ')
PASSWORD = input('Password: ')

client = DocumentCloud(USERNAME, PASSWORD)