District Level Report Bhavnagar

Author

Ayush Patel

Published

August 23, 2022

Introduction - Bhavnagar

This report aims to provide a birds eye view of the district through the lens of village amenities data released by census in 2011. Before moving towards the descriptive insights from the census data, here is what pops up when a search is executed for Bhavnagar district Gujarat on wikipedia.



Summary Statistics

Total Number of Villages: 793

Total Number of Gram Panchayat: 680

Total Number of Sub Districts: 11

Total Population : 1.697964^{6}

Statistical Summaries at the subdistrict level

Sub District Total Population Total SC Population Total ST Population Total Area of Vilalges Total Area Sown (Net)
Bhavnagar 144056 4307 721 89684.06 34554.84
Botad 156291 11722 301 68227.83 53769.02
Gadhada 156155 10040 264 81322.39 54343.19
Gariadhar 84327 7918 292 45667.93 36994.86
Ghogha 88769 1919 101 42590.98 28959.14
Mahuva 344815 12147 764 121468.72 87772.03
Palitana 165774 11304 301 69034.89 42299.77
Sihor 151662 11220 339 68005.95 46245.35
Talaja 271056 7338 146 83117.94 61816.86
Umrala 70719 7091 91 38619.42 29113.08
Vallabhipur 64340 3665 88 55248.29 43306.59

Population and Geographical Area

It is of interest to look into which are the most densely populated villages. We can do this by creating a simple scatter plot between population of village and the total geographical area of a village.


Irrigation for Agriculture

The census provides the net area sown (hectares) in a village along with area irrigated with water source in hectares. The area under irrigation may be affected by several factors.

Area Sown vs Area under Irrigation


A distribution for the percentage of area irrigated will be interesting to look at.

Understanding what drives area under irrigation

Much is heard about rain fed agriculture in India. There are several factors that can affect area under irrigation - ranging from government supports, demographics, distance from urban clusters and several known and unknown variables. With the given data we can check if the following variables have any relation with area under irrigation:

  • Percentage of Marginalised group population in village
  • Distance from Major government offices
  • Distance from urban center
  • Total population of a village

A simple Linear regression to see if the above explanation has any merit

Dependent variable:
perc_irrigated_over_net_sown
total_population_of_village 0.0005
(0.0005)
perc_marginalised_pop 0.001
(0.127)
district_head_quarter_distance_in_km 0.031
(0.059)
sub_district_head_quarter_distance_in_km -0.226
(0.184)
nearest_statutory_town_distance_in_km 0.195
(0.209)
sub_district_nameBotad 12.975**
(6.564)
sub_district_nameGadhada 23.855***
(5.763)
sub_district_nameGariadhar -2.011
(5.921)
sub_district_nameGhogha 22.396***
(4.790)
sub_district_nameMahuva 7.346
(5.958)
sub_district_namePalitana 7.682
(5.047)
sub_district_nameSihor 9.864**
(4.407)
sub_district_nameTalaja 36.574***
(4.625)
sub_district_nameUmrala 12.509**
(5.461)
sub_district_nameVallabhipur -8.814*
(5.061)
Constant 28.800***
(4.281)
Observations 781
R2 0.239
Adjusted R2 0.225
Residual Std. Error 23.432 (df = 765)
F Statistic 16.054*** (df = 15; 765)
Note: p<0.1; p<0.05; p<0.01

Model Diagnostic plots

Distribution of Redsiduals


Residuals vs Fitted

Note

This is to serve as a minimal example of creating parameterised reports with .rmd/.qmd files. This document is in no way analytically or statistically rigorous.