How to Read CSV Files with Semi-Colons as Separators in Pandas?

Separating Data with Semi-Colons in Pandas

When reading a .csv file with pandas, the default separator for columns is a comma (,). However, if your file uses a different separator, such as a semi-colon (;), you'll need to specify this in the parameters when using the read_csv function.

Consider the following .csv file format:

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

To read this file with pandas and split the values into columns based on the semi-colon separator, use the following code:

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

# Specify the file path
csv_path = "C:...."

# Set the separator character to ';'
data = pd.read_csv(csv_path, sep=';')

# Print the resulting DataFrame to check if the values are split into columns
print(data)</code>

By passing sep=';', you're explicitly telling pandas to use the semi-colon as the delimiter. This way, the data will be parsed correctly and organized into individual columns.

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