How to Read Specific Columns from a CSV File Efficiently?

Selective Column Reading in a CSV File with the csv Module

Understanding the Problem

Reading specific columns from a CSV file can be a common task in data processing. However, accessing columns by their number, as attempted in the given code, may lead to unexpected results.

Addressing the Mistake

The mistake in the provided code lies in placing the print statement outside the for loop. Consequently, only the last iteration's result is printed, which is the last column of the CSV file.

Code Correction

To fix this issue, the print statement should be moved inside the loop to print each row's specific columns:

for row in reader:
    content = list(row[i] for i in included_cols)
    print(content)

Advantages of the Pandas Module

While the adjusted code can accomplish the task, it lacks the convenience and efficiency of the pandas module. Pandas provides an elegant and versatile solution for CSV file manipulation.

Pandas for Selective Column Reading

Using pandas, reading a specific column from a CSV file becomes effortless:

import pandas as pd

df = pd.read_csv(csv_file)

# Save column data to a variable
column_data = df['column_name']

Simplified Code

The Pandas solution significantly simplifies the code:

import pandas as pd

df = pd.read_csv(csv_file)

# Save specific columns as a list
specific_columns = ['ID', 'Name', 'Zip', 'Phone']
data = df[specific_columns].values.tolist()

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