9.12.2 Reading CSV Files into Pandas DataFrames

• Here, we demonstrate pandas’ ability to load files in CSV format, then perform some basic data-analysis tasks

Datasets

• Enormous variety of free datasets available online
• Rdatasets repository provides links to over 1100 free datasets in comma-separated values (CSV) format

  https://vincentarelbundock.github.io/Rdatasets/datasets.html

• pydataset module specifically for accessing Rdatasets

  https://github.com/iamaziz/PyDataset

• Another large source of datasets is

  https://github.com/awesomedata/awesome-public-datasets

• A commonly used machine-learning dataset for beginners is the Titanic disaster dataset

Working with Locally Stored CSV Files

• File we'll process in this example

!cat accounts.csv

100,Jones,24.98
200,Doe,345.67
300,White,0.0
400,Stone,-42.16
500,Rich,224.62

• Load a CSV dataset into a DataFrame with the pandas function read_csv
• names argument specifies the DataFrame’s column names
  • Without this argument, read_csv assumes that the CSV file’s first row is a comma-delimited list of column names

import pandas as pd

df = pd.read_csv('accounts.csv', 
                 names=['account', 'name', 'balance'])

df

	account	name	balance
0	100	Jones	24.98
1	200	Doe	345.67
2	300	White	0.00
3	400	Stone	-42.16
4	500	Rich	224.62

• To save a DataFrame to a file using CSV format, call DataFrame method to_csv
• index=False indicates that the row names (0–4 at the left of the DataFrame’s output above are not written to the file
• Resulting file contains the column names as the first row

df.to_csv('accounts_from_dataframe.csv', index=False)

!cat accounts_from_dataframe.csv

account,name,balance
100,Jones,24.98
200,Doe,345.67
300,White,0.0
400,Stone,-42.16
500,Rich,224.62

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