Keywords: unpivot python stack
Over ArcGIS or a .dbf file, the maximum number of columns are 256.
An extensive Pandas dataframe with more than 256 attributes, could be truncated if directly is converted into a GIS table.
The size of the transformed unpivot file, could be much bigger than the original pivot file.
# -*- coding: UTF-8 -*-
# Name: UnpivotTable.py
# Description: unpivot a multiple column table into a table with multiple records
# Requirements: Python 3+, pandas
# Repository: https://github.com/rcfdtools/R.GISPython/tree/main/UnpivotTable
# License: https://github.com/rcfdtools/R.GISPython/wiki/License
# Libraries
import pandas as pd
# General variables
pivot_table = 'df_prec_ANA_20230216.csv' # Current IDEAM records file with multiple columns
date_field = 'Date' # Column date name
var_name = 'Codigo' # Column code name
value_name = 'Valor' # Column value name
# Procedure
df = pd.read_csv(pivot_table, low_memory=False, parse_dates=[date_field], dayfirst=True) # Check your right day position in the date field
print(df.info(), '\n')
print(df.dtypes, '\n')
print(df, '\n')
df_unpivot = pd.melt(df, id_vars=date_field, var_name=var_name, value_name=value_name, ignore_index = True)
print(df_unpivot, '\n')
df_unpivot.index.name = 'Id'
df_unpivot.to_csv('unpivot_'+pivot_table)`
- https://towardsdatascience.com/4-tricks-you-should-know-to-parse-date-columns-with-pandas-read-csv-27355bb2ad0e
- https://www.statology.org/pandas-unpivot/
- https://sparkbyexamples.com/pandas/pandas-unpivot-dataframe/
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