Creating DataFrames Cookbook

Combining multiple Series into a DataFrame Combining multiple Series to form a DataFrame Converting a Series to a DataFrame Converting list of lists into DataFrame Converting list to DataFrame Converting percent string into a numeric for read_csv Converting scikit-learn dataset to Pandas DataFrame Converting string data into a DataFrame Creating a DataFrame from a string Creating a DataFrame using lists Creating a DataFrame with different type for each column Creating a DataFrame with empty values Creating a DataFrame with missing values Creating a DataFrame with random numbers Creating a DataFrame with zeros Creating a MultiIndex DataFrame Creating a Pandas DataFrame Creating a single DataFrame from multiple files Creating empty DataFrame with only column labels Filling missing values when using read_csv Importing Dataset Initialising a DataFrame using a constant Initialising a DataFrame using a dictionary Initialising a DataFrame using a list of dictionaries Inserting lists into a DataFrame cell Keeping leading zeroes when using read_csv Parsing dates when using read_csv Preventing strings from getting parsed as NaN for read_csv Reading data from GitHub Reading file without header Reading large CSV files in chunks Reading n random lines using read_csv Reading space-delimited files Reading specific columns from file Reading tab-delimited files Reading the first few lines of a file to create DataFrame Reading the last n lines of a file Reading URL using read_csv Reading zipped csv file as a DataFrame Removing Unnamed:0 column Resolving ParserError: Error tokenizing data Saving DataFrame as zipped csv Skipping rows without skipping header for read_csv Specifying data type for read_csv Treating missing values as empty strings rather than NaN for read_csv

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Reading data from GitHub in Pandas

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Creating DataFrames Cookbook

Mar 9, 2022

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local_offer Python●Pandas

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Table of Contents

To read data from a GitHub page in Pandas, supply the URL to the read_csv(~) method:


        
        
            
                
                
                    import pandas as pd
url = "https://raw.githubusercontent.com/SkyTowner/sample_data/main/pandas/simple_dataset.csv"
df = pd.read_csv(url)
df
                
            
               A  B  C
0  1  2  3
1  4  5  6
2  7  8  9

Notice how the URL begins with raw. In order to retrieve this URL, visit the GitHub page containing your dataset. In our case, this is as follows:


        
        
            
                
                
                    https://github.com/SkyTowner/sample_data/blob/main/pandas/simple_dataset.csv

Next, click on the "Raw" button at the top in order to get the plain CSV file.

Pandas | read_csv method

Pandas read_csv(~) method reads a file, and parses its content into a DataFrame.