Reading a .csv file with Python and creating a DataFrame
Posted On 19 March 2021
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
# If you want to have these values printed in the console
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