Accessing Rows and Columns
If you need to get particular rows and columns, you can easily combine both methods learned previously, in any order. That is, you can get certain row, and then choose the columns you need, or vice versa. Look at the example below, and compare both outputs.
12345678# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Get the 'mileage' column value of the first row print(df[0:1]['mileage']) print(df['mileage'][0])
Remember that you need to use slicing even for getting a single row.
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Completion rate improved to 3.33Accessing Rows and Columns
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If you need to get particular rows and columns, you can easily combine both methods learned previously, in any order. That is, you can get certain row, and then choose the columns you need, or vice versa. Look at the example below, and compare both outputs.
12345678# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Get the 'mileage' column value of the first row print(df[0:1]['mileage']) print(df['mileage'][0])
Remember that you need to use slicing even for getting a single row.
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