How to Read a CSV File with Semicolon Separated Values Using Pandas?

How to Separate Columns in a CSV File with Pandas

When importing a CSV file with pandas, users may encounter situations where the values are separated by a character other than a comma. To address this challenge, pandas provides the option to specify a separator using the sep parameter within the read_csv function.

Problem:

Suppose a CSV file follows the following format, where values are separated by semicolons:

a1;b1;c1;d1;e1;...
a2;b2;c2;d2;e2;...

Response:

To read the file correctly and split the values into columns based on semicolons, use the following code:

<code class="python">import pandas as pd

csv_path = "C:..."
data = pd.read_csv(csv_path, sep=';')</code>

The sep parameter specifically instructs pandas to use a semicolon as the separator, ensuring that the data is parsed into multiple columns. By default, pandas uses a comma as the separator, so the original code failed to separate the values correctly.

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