Make,Colour,Odometer (KM),Doors,Price

Toyota,White,150043,4,"$4,000.00"

Honda,Red,87899,4,"$5,000.00"

Toyota,Blue,32549,3,"$7,000.00"

BMW,Black,11179,5,"$22,000.00"

Nissan,White,213095,4,"$3,500.00"

Toyota,Green,99213,4,"$4,500.00"

Honda,Blue,45698,4,"$7,500.00"

Honda,Blue,54738,4,"$7,000.00"

Toyota,White,60000,4,"$6,250.00"

Nissan,White,31600,4,"$9,700.00"

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)

```

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*

`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.

- [Importing and Exporting Data in Pandas](import-export.md)