The motivation of this project was just to learn and play with the grammer of Shiny, HighCharts and Leaflets. The 2011 census data for
around 500 cities of India were analysed and was visualised using Maps, Columns and Tree Map. The data cities_r2.csv was analysed on important variables such as
sex ratio and effective literacy rate in order to show which all cities and states least females to males ratio and literates compared to the whole population of the city or state.
'name_of_city' : Name of the City
'state_code' : State Code of the City
'state_name' : State Name of the City
'dist_code' : District Code where the city belongs ( 99 means multiple district )
'population_total' : Total Population
'population_male' : Male Population
'population_female' : Female Population
'0-6_population_total' : 0-6 Age Total Population
'0-6_population_male' : 0-6 Age Male Population
'0-6_population_female' : 0-6 Age Female Population
'literates_total' : Total Literates
'literates_male' : Male Literates
'literates_female' : Female Literates
'sex_ratio' : Sex Ratio
'child_sex_ratio' : Sex ratio in 0-6
'effective_literacy_rate_total' : Literacy rate over Age 7
'effective_literacy_rate_male' : Male Literacy rate over Age 7
'effective_literacy_rate_female': Female Literacy rate over Age 7
'location' : Lat,Lng
'total_graduates' : Total Number of Graduates
'male_graduates' : Male Graduates
'female_graduates' : Female Graduates