[1081] The syntax and usage for the drop_duplicates and duplicated functions in a GeoDataFrame in GeoPandas.

Certainly! Here's the syntax and usage for the drop_duplicates and duplicated functions in a GeoDataFrame in GeoPandas.

drop_duplicates Function

The drop_duplicates method removes duplicate rows based on one or more columns.

Syntax:

GeoDataFrame.drop_duplicates(subset=None, keep='first', inplace=False)

Parameters:

• subset (optional): Column label or sequence of labels to consider for identifying duplicates. Defaults to all columns.
• keep (optional): Determines which duplicates to mark:
  • 'first': Drop duplicates except for the first occurrence.
  • 'last': Drop duplicates except for the last occurrence.
  • False: Drop all duplicates.
• inplace (optional): If True, do operation inplace and return None.

Example:

import geopandas as gpd
from shapely.geometry import Point
 
# Sample GeoDataFrame
data = {'ID': [1, 2, 2, 3, 4, 4, 4], 'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank', 'Grace'], 'geometry': [Point(1, 2), Point(2, 3), Point(3, 4), Point(4, 5), Point(5, 6), Point(6, 7), Point(7, 8)]}
gdf = gpd.GeoDataFrame(data, crs="EPSG:4326")
 
# Drop duplicates based on the 'ID' column, keeping the first occurrence
gdf_unique = gdf.drop_duplicates(subset='ID', keep='first')
 
print(gdf_unique)

duplicated Function

The duplicated method returns a Boolean Series indicating duplicate rows.

Syntax:

GeoDataFrame.duplicated(subset=None, keep='first')

Parameters:

• subset (optional): Column label or sequence of labels to consider for identifying duplicates. Defaults to all columns.
• keep (optional): Determines which duplicates to mark:
  • 'first': Mark duplicates as True except for the first occurrence.
  • 'last': Mark duplicates as True except for the last occurrence.
  • False: Mark all duplicates as True.

Example:

# Identify duplicate rows based on the 'ID' column
duplicates = gdf.duplicated(subset='ID', keep='first')
 
print(duplicates)

Explanation:

• drop_duplicates: Removes duplicate rows from the GeoDataFrame based on specified columns.
• duplicated: Identifies duplicate rows and returns a Boolean Series indicating which rows are duplicates.

These methods are useful for data cleaning and ensuring that your GeoDataFrame contains unique entries as required.

Feel free to try these examples and let me know if you need any further assistance!