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Data Processing Snippets

Use these snippets as starting points for common data cleanup tasks.

Read A CSV​

import pandas as pd

df = pd.read_csv("input.csv")
print(df.head())
print(df.columns)

Read An Excel File​

import pandas as pd

df = pd.read_excel("input.xlsx")
print(df.head())

Remove Duplicate Rows​

import pandas as pd

df = pd.read_csv("input.csv")
clean = df.drop_duplicates()
clean.to_csv("deduplicated.csv", index=False)

Clean Column Names​

import pandas as pd

df = pd.read_csv("input.csv")
df.columns = (
    df.columns
    .str.strip()
    .str.lower()
    .str.replace(" ", "_")
)
df.to_csv("clean_columns.csv", index=False)

Group And Summarize​

import pandas as pd

df = pd.read_csv("sales.csv")
summary = (
    df.groupby("region")
    .agg(total_sales=("amount", "sum"), order_count=("amount", "count"))
    .reset_index()
)
summary.to_csv("summary_by_region.csv", index=False)

Merge Two CSV Files​

import pandas as pd

orders = pd.read_csv("orders.csv")
customers = pd.read_csv("customers.csv")

merged = orders.merge(customers, on="customer_id", how="left")
merged.to_csv("orders_with_customers.csv", index=False)

Prompt To Adapt A Snippet​

Adapt this pandas snippet to my file.
Input file:
Columns:
Cleaning rules:
Output file:
Please include checks for missing columns and explain how to run it.