Reading a CSV file using Python
Problem
You wish to open a CSV file in your Python program in order to read some data that are not volatile. In this post we will see how to use one of the libraries out there that is designed to read/save different file types like CSV, Excel, Json.
Solution
The pandas library. Let’s assume there is a CSV file with the following content:
cars, color
Acura, blue
Alfa Romeo, white
Aston Martin, white
Audi, black
Bentley, gold
BMW, green
Buick, yellow
The csv file is named ‘data.csv’ and is placed in the same directory with the Python program. The code to read it is as follows:
import pandas as pd
data_frame = pd.read_csv('data.csv')
print(data_frame.to_string())
To execute the above:
python3 open_csv.py
The output:
Using different delimiter
What if the file is not comma separated but with a semicolon or a tab? As per read_csv() documentation, the delimiter symbol can be passed as an argument. For example, if we change the input ‘data.csv’ to the following:
airplane max_altitude
Turboprop Aircraft 35,000 feet
Piston Aircraft 15,000 feet
Jets 49,000 feet
Now there are 2 columns and 3 lines. Each line has a tab character (\t) as separator for the values. We used this due to the use of comma as part of the value in the max_altitude column. The change needed in the code is simply passing the delimiter =’\t’ as shown below:
import pandas as pd
data_frame = pd.read_csv('data.csv', delimiter='\t')
print(data_frame.to_string())
Running it:
python3 open_csv.py
The output is:
ignoring header
The first line usually is used for indicating the headers. What if you wish to ignore it or it doesn’t exist in the first place? It can be done by passing the header=None argument as follows:
import pandas as pd
data_frame = pd.read_csv('data.csv', delimiter='\t',header=None)
print(data_frame.to_string())
Conclusion
Python and pandas library is a great combination and choice when it comes to tasks like reading a text file or saving it. You can have a look on their getting started page for more information.
See more Python tutorials.