Python筛选DataFrame指定经纬度范围数据并导出CSV

Hey there! Let's wrap up your task of filtering geographic data and exporting the results. You've already started with importing pandas—here's the complete, working code plus clear breakdowns:

Complete Working Code #

import pandas as pd

# Read the original CSV file into a DataFrame
df = pd.read_csv("your_input_file.csv")  # Replace with your actual file path

# Filter rows where startlat is between 18-20 AND startlon is between 72.5-75
filtered_df = df[(df['startlat'].between(18, 20)) & (df['startlon'].between(72.5, 75))]

# Export the filtered DataFrame to a new CSV file
filtered_df.to_csv("filtered_geo_data.csv", index=False)  # index=False removes the extra index column

Key Breakdowns #

• Reading the CSV: Make sure to replace "your_input_file.csv" with the actual path to your CSV file (relative or absolute).
• Filtering Logic:
  • We use pd.Series.between() to cleanly check if values fall within the specified ranges—it's more readable than writing (df['startlat'] >=18) & (df['startlat'] <=20).
  • The & operator ensures both conditions are met. Don't forget the parentheses around each condition—they're required for correct operator precedence!
• Exporting: The index=False parameter is important because it prevents pandas from adding an extra column with the row index to your output CSV.

Optional Checks (To Avoid Headaches) #

• Verify your column names match exactly: Run print(df.columns) to double-check that startlat and startlon are spelled correctly (pandas is case-sensitive!).
• Handle missing values: If your dataset has NaN values in these columns, add .dropna(subset=['startlat', 'startlon']) before filtering to exclude rows with missing coordinates:

  df_clean = df.dropna(subset=['startlat', 'startlon'])
  filtered_df = df_clean[(df_clean['startlat'].between(18,20)) & (df_clean['startlon'].between(72.5,75))]
  

内容的提问来源于stack exchange，提问作者Ajinkya