1. Loading the data from IHDS and Census survey of India

householdh_marginal_filename = "path_to_household_marginals"
individuals_marginal_filename = "path_to_individual_marginals"

ihds_individuals_filename = "path_to/36151-0001-Data.tsv"
ihds_household_filename = "path_to/36151-0002-Data.tsv"

2. Geojson Spatial Data

Setting the data sources for geojson spatial data for wards.
Current source: [Municipal Spatial Data]
This Repository will contain the spatial data of all the Municipalities that has been scraped from their websites and other sources. Do note, that the wards in these datasets, are usually the Municipal wards, and not the Census wards. Geojson ward names should match with the ward names in the ward-wise population file (See Next Steps), so that one can use it as a primary key. If they don't match please rename them accordingly.For example if the ward name in geojson is Ward-1 and in population file is Ward 1, then rename it to Ward-1 in the population file.

# Example geojson using Kolkata as the city
admin_units_geojson_filename = "https://raw.githubusercontent.com/datameet/Municipal_Spatial_Data/master/Kolkata/kolkata.geojson"

3. Loading the Population Density Data

Current source for population density data: [Link] [Note: Please unzip to access the .csv file]

population_density_filename = "/path_to/ind_pd_2020_1km_ASCII_XYZ.csv"

4. Loading ward wise population

admin_units_population_filename="path_to_file"
#after loading the data, one can specify the total population of each ward using column name TOT_P in their respective datadrames

Current Source for ward-wise population: CensusGov

To get ward wise lat-long, one can use either of the following sources:

https://github.com/geopy/geopy
https://www.mapmyindia.com/api
https://developers.google.com/maps/documentation/geocoding/overview

Next we would merge the ward-wise population with the lat-long data (keeping Ward Name/no. as the unique key)

Sample Format:

Ward	Latitude	Longitude	TOT_P
Kolkata Ward 2	88.34	83.34	111000
Kolkata Ward 3	85.33	89.77	99991

5. Setting the state and district ID

State and district ID can be found out using Census MetaData found [here].

# select state id
state_id = 19 # West Bengal

#Select distid within state
district_ids = [17] # Kolkata