How to Import a Semicolon-Separated CSV File into Pandas?

Reading a File with Semi-Colon Separator in Pandas

When importing a .csv file into Python using pandas, it's crucial to account for different separators. In cases where the file is separated by semicolons (;), pandas requires explicit specification.

In the given example, the user attempts to read a file with semicolon-separated values using the following code:

from pandas import *
csv_path = "C:...."
data = read_csv(csv_path)

However, this fails to split the values into separate columns, as pandas defaults to comma (,) as the separator. The resulting dataframe appears as a single column of comma-separated values.

To resolve this issue, specify the separator using the sep parameter:

data = read_csv(csv_path, sep=';')

This change ensures that the values are split based on the semicolon character, creating individual columns for each value. The dataframe will now correctly display the data in separate columns, allowing for easy analysis and manipulation.

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