Reading a .csv file with Python and creating a DataFrame
In this chapter I will dive into reading the data in .csv file and creating a DataFrame. A .csv file stands for comma-separated value, so it simply contains a set of values separated by a comma where each line is a new record in plain text.
For this exercise we first make a Python script ‘Read_csv.py’. Once opened in an text editor or a code editor such as Visual Studio Code (macOS, Windows, Linux), PyCharm (macOS, Windows, Linux) and many others, we can start writing code.
You can use the ‘restaurants.csv’ file
# Read a .csv file and store the data in a DataFrame # Import pandas import pandas as pd # read the content of 'restaurants.csv' and store it into a DataFrame 'df' df = pd.read_csv('restaurants.csv') # Show the first 5 rows of the DataFrame. Default value is 5 df.head() # If you want to have these values printed in the console print(df.head())
Depending on your settings, in line 7 you might want to use the path to the file. Which in my case is: /Users/hr/Documents/restaurants.csv
Running our python script results in:
name kitchen review rating 0 Sumo Japanese Good delicious sushi 8 1 Fried chips Snackbar Tasty but a bit too fat 5 2 Oikos Greek That was fantastic 8 3 The Garden British So so 6 4 McOnald American horrible 3
Pandas automatically turns the .csv file into a DataFrame. A DataFrame can be seen as a table with data in it.
For more reference: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.head.html