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Importing and Exporting Data in Pandas
Importing Data from a CSV
We can create Series and DataFrame in pandas, but often we have to import the data which is in the form of .csv (Comma Separated Values), a spreadsheet file or similar tabular data file format.
pandas allows for easy importing of this data using functions such as read_csv() and read_excel() for Microsoft Excel files.
Note: In case you want to get the information from a Google Sheet you can export it as a .csv file.
The read_csv() function can be used to import a CSV file into a pandas DataFrame. The path can be a file system path or a URL where the CSV is available.
import pandas as pd
car_sales_df= pd.read_csv("Datasets/car-sales.csv")
print(car_sales_df)
Make Colour Odometer (KM) Doors Price
0 Toyota White 150043 4 $4,000.00
1 Honda Red 87899 4 $5,000.00
2 Toyota Blue 32549 3 $7,000.00
3 BMW Black 11179 5 $22,000.00
4 Nissan White 213095 4 $3,500.00
5 Toyota Green 99213 4 $4,500.00
6 Honda Blue 45698 4 $7,500.00
7 Honda Blue 54738 4 $7,000.00
8 Toyota White 60000 4 $6,250.00
9 Nissan White 31600 4 $9,700.00
You can find the dataset used above in the Datasets folder.
Note: If you want to import the data from Github you can't directly use its link, you have to first obtain the raw file URL by clicking on the raw button present in the repo
Exporting Data to a CSV
pandas allows you to export DataFrame to .csv format using .to_csv(), or to a Excel spreadsheet using .to_excel().
car_sales_df.to_csv("exported_car_sales.csv")
Running this will save a file called exported_car_sales.csv to the current folder.