如何用Pandas提取子集与超集CSV的交集列及超集指定列？

Here's a straightforward, efficient way to get the exact result you're looking for using Pandas:

Step 1: Set Up Pandas #

First, make sure Pandas is installed (run pip install pandas if you haven't already), then import it:

import pandas as pd

Step 2: Load Your CSV Files #

Read both your super.csv (the full dataset) and sub.csv (the subset of Num values) into Pandas DataFrames:

# Load the super set with Num and Val columns
df_super = pd.read_csv('super.csv')

# Load the subset with only Num column
df_sub = pd.read_csv('sub.csv')

Step 3: Filter for Matching Rows #

Use Pandas' built-in isin() method to filter the super DataFrame down to only rows where Num exists in the subset:

# Extract the list of Num values we want to keep
target_nums = df_sub['Num'].tolist()

# Filter the super DataFrame to retain only matching rows
result_df = df_super[df_super['Num'].isin(target_nums)]

Step 4: Output the Result #

Print the data in your requested format, or save it to a new CSV if needed:

# Print the result with the exact format you specified
print("Num , Val")
for _, row in result_df.iterrows():
    print(f"{row['Num']},{row['Val']}")

# Optional: Save to a new CSV file
result_df.to_csv('intersection_result.csv', index=False)

Example Output #

When you run the code, you'll get:

Num , Val
2,25
4,87

This method leverages Pandas' optimized filtering capabilities, so it works smoothly even if your datasets grow larger over time.

内容的提问来源于stack exchange，提问作者Vatsalya Tandon