Validation Summary¶

Use this notebook to confirm that input records are complete, coordinate values are reasonable, and output naming conventions follow the intended workflow.

In [ ]:

# Simple validation checks
name_check = sample_data['Name'].isna().sum()
coord_check = sample_data[['Latitude', 'Longitude']].isna().sum().sum()
remarks_check = sample_data['Remarks'].eq('Temporary GCP').sum() + sample_data['Remarks'].eq('Permanent GCP').sum()

print(f"Missing names: {name_check}")
print(f"Missing coordinates: {coord_check}")
print(f"Valid remarks entries: {remarks_check}")

# Simple validation checks name_check = sample_data['Name'].isna().sum() coord_check = sample_data[['Latitude', 'Longitude']].isna().sum().sum() remarks_check = sample_data['Remarks'].eq('Temporary GCP').sum() + sample_data['Remarks'].eq('Permanent GCP').sum() print(f"Missing names: {name_check}") print(f"Missing coordinates: {coord_check}") print(f"Valid remarks entries: {remarks_check}")

In [ ]:

missing_values = sample_data.isna().sum()
missing_values

missing_values = sample_data.isna().sum() missing_values

In [ ]:

import pandas as pd
from pathlib import Path

# Example placeholder for validation logic
sample_data = pd.DataFrame(
    {
        'Name': ['GCP1', 'GCP2', 'P1'],
        'Latitude': [12.34, 12.35, 12.36],
        'Longitude': [77.12, 77.13, 77.14],
        'Remarks': ['Temporary GCP', 'Temporary GCP', 'Permanent GCP']
    }
)

sample_data.head()

import pandas as pd from pathlib import Path # Example placeholder for validation logic sample_data = pd.DataFrame( { 'Name': ['GCP1', 'GCP2', 'P1'], 'Latitude': [12.34, 12.35, 12.36], 'Longitude': [77.12, 77.13, 77.14], 'Remarks': ['Temporary GCP', 'Temporary GCP', 'Permanent GCP'] } ) sample_data.head()

GCP Validation Notebook¶

This notebook is designed to review the quality of GCP/PGCP outputs before final reporting. It checks for missing values, coordinate consistency, naming issues, and output completeness.