combine files.py

combine files.py

import glob as glob
import pandas as pd
#define path to CSV files
path = r'ndvi data/*.csv'

#identify all CSV files
all_files = glob.glob(path)

#merge all CSV files into one DataFrame
fireNDVI = pd.concat((pd.read_csv(f) for f in all_files), ignore_index=True)

##############################
# Get a list of missing values
missing_values = list(set(gdf['OBJECTID'].unique().tolist()) - set(fireNDVI['OBJECTID'].unique().tolist()))
# Subset gdf to isolate the missing values
missing_rows = gdf[gdf['OBJECTID'].isin(missing_values)]
print(f"There are {gdf['OBJECTID'].nunique() - fireNDVI['OBJECTID'].nunique()} missing OBJECTIDs")
print(f"These missing values are {missing_values}")

##############################
# Download the NDVI for the missing records

# Collect all 
collectAllNDVI(missing_rows)
print('Complete.')

##############################
# Re-combine the data files include any missing files
# identify all CSV files in the path
all_files = glob.glob(path)

#merge all CSV files into one DataFrame
fireNDVI = pd.concat((pd.read_csv(f) for f in all_files), ignore_index=True)