Got it, let's work through this problem. You want to populate the Result column in your first Excel file by matching the svc_no values with a second Excel file. Here's a straightforward way to do this with Pandas:

Step-by-Step Solution #

1. Import Pandas and Load Your Files #

First, we'll read both Excel files into Pandas DataFrames. Make sure to replace the file paths with your actual file names.

import pandas as pd

# Load the main file (where you need to fill the Result column)
df_main = pd.read_excel("your_main_file.xlsx")

# Load the source file (contains the matching Result data for svc_no)
df_source = pd.read_excel("your_source_file.xlsx")

2. Match Data and Fill the Result Column #

You have two common approaches here—choose the one that fits your needs:

Option 1: Use merge (Best for Matching Multiple Columns)

This method is flexible if you ever need to pull more than just the Result column later. We'll do a left join to keep all rows from your main file, even if there's no matching svc_no in the source.

# Merge the two DataFrames on svc_no, keeping only the Result column from the source
df_merged = pd.merge(
    df_main,
    df_source[["svc_no", "Result"]],  # Adjust "Result" to your source column name if needed
    on="svc_no",
    how="left",
    suffixes=("", "_source")
)

# Populate the Result column in the main DataFrame
df_main["Result"] = df_merged["Result_source"].fillna("")  # Use fillna("N/A") if you want a placeholder

# Save the updated file
df_main.to_excel("main_file_with_results.xlsx", index=False)

Option 2: Use map (Simpler for Single Column Matching)

If you only need to pull the Result column, this is a more concise approach. We'll create a dictionary mapping svc_no to its corresponding Result value.

# Create a mapping dictionary: svc_no -> Result
result_mapping = df_source.set_index("svc_no")["Result"].to_dict()

# Fill the Result column in the main DataFrame
df_main["Result"] = df_main["svc_no"].map(result_mapping).fillna("")

# Save the updated file
df_main.to_excel("main_file_with_results.xlsx", index=False)

3. Important Notes to Avoid Issues #

• Data Type Consistency: Ensure svc_no is the same data type in both files (e.g., both strings or both integers). If not, convert them:

  df_main["svc_no"] = df_main["svc_no"].astype(str)
  df_source["svc_no"] = df_source["svc_no"].astype(str)
  

• Duplicate svc_no: If your source file has duplicate svc_no entries, remove them first to avoid unexpected matches:

  df_source = df_source.drop_duplicates(subset="svc_no")
  

• Missing Matches: The fillna("") ensures any svc_no without a match in the source will have an empty Result cell. You can replace the empty string with something like "No Match" if preferred.

内容的提问来源于stack exchange，提问作者Ganzo Palumi