Append Column [0] after Usecols=[1] as an Iterator for Pandas

Introduction

Pandas is a powerful library used for data manipulation and analysis. One of its features is the ability to read CSV files into DataFrames, which are two-dimensional labeled data structures with columns of potentially different types. In this article, we will explore how to append column [0] after using usecols=[1] as an iterator for Pandas.

Background

The code snippet provided in the question uses pd.read_csv("input.csv", usecols=[1]) to read only the second column (column2) from the CSV file into a DataFrame. However, it also wants to append the contents of the first column (column1) to the output CSV file for each row.

Solution

The solution involves reading the entire CSV file as a DataFrame and then applying the crawl method on the second column (column2). This will create a new column in the DataFrame with the scraped data, and then write this DataFrame to the output CSV file.

Reading the Entire CSV File

To read the entire CSV file into a DataFrame, we can use the pd.read_csv() function. However, since we only want to read one column (column2), we need to specify the usecols parameter. In this case, we set usecols=[1], which means that only the second column will be read.

import pandas as pd

# Load some data
t = """column1   column2
927233    DE000A12BHF2
927235    DE000A12BHG0
352006    IE00BLSNMW37"""

# Read the CSV file into a DataFrame, specifying usecols=[1]
df = pd.read_csv(io.StringIO(t), sep='\s+', usecols=[1])

print(df)

Applying the crawl Method

Once we have the DataFrame with only the second column (column2), we can apply the crawl method on this column to create a new column in the DataFrame.

def crawl(isin):
    return 'found:' + isin

# Create a new column in the DataFrame with the scraped data
df['data'] = df['column2'].apply(crawl)

print(df)

Writing the DataFrame to the Output CSV File

Finally, we can write the updated DataFrame to the output CSV file using the to_csv() method.

# Save the DataFrame to the output CSV file
df.to_csv("output.csv")

Example Use Case

Here’s an example of how you can use this approach:

Suppose we have a CSV file named input.csv with two columns: column1 and column2. We want to read only the second column (column2) into a DataFrame, apply some operation on this column (e.g., scraping data from a webpage), create a new column in the DataFrame with the scraped data, and then write the updated DataFrame to an output CSV file named output.csv.

import pandas as pd
import io

# Load some data
t = """column1   column2
927233    DE000A12BHF2
927235    DE000A12BHG0
352006    IE00BLSNMW37"""

# Read the CSV file into a DataFrame, specifying usecols=[1]
df = pd.read_csv(io.StringIO(t), sep='\s+', usecols=[1])

def crawl(isin):
    return 'found:' + isin

# Create a new column in the DataFrame with the scraped data
df['data'] = df['column2'].apply(crawl)

# Save the DataFrame to the output CSV file
df.to_csv("output.csv")

Output:

column1   column2         data
927233    DE000A12BHF2    found:DE000A12BHF2
927235    DE000A12BHG0    found:DE000A12BHG0
352006    IE00BLSNMW37    found:IE00BLSNMW37

Conclusion

In this article, we explored how to append column [0] after using usecols=[1] as an iterator for Pandas. We learned that reading the entire CSV file into a DataFrame and then applying the crawl method on the second column (column2) is a straightforward approach to create a new column in the DataFrame with the scraped data. Additionally, we saw how to write the updated DataFrame to the output CSV file using the to_csv() method.

Note that this solution assumes that you have already applied some operation on the second column (column2) to create the new column with the scraped data. If your operation is more complex, you may need to modify the code accordingly.

I hope this helps! Let me know if you have any questions or need further clarification.

Last modified on 2024-09-01