After taking the session of CampusX DSMP Program. I decided that this would be a good project to improve my Data Wrangling and Data Interpretation ability.
- Data is not appropriate or absolute to belive. I just used it for practicing purpose.
Inspired from CampusX a Data Science YouTube channel.
- Plot a
scatter_mapbox
for each States and Districts. - Plot a
pie chart
formale-female
distributions in States. Do this only for States.
- Plot a
scatter_mapbox
for each States and Districts. - Plot a
pie chart
formale-female
distribution in States.
- This data contains two caste groups
SC & ST
. So we can plot the only thepie charts
for each States. - For Districts we can plot the
nested pie plot
for each States's Districts.*
- This contains maybe five religions overall. So we have again plot the
nested pie plot
for each States and Districts.
- Plot some default
scatter plot
with plotly to display many feature analysis in one graph. - After analysing the
Rough Analysis.py
graphs I found thatLitracy
columns does not depict the way it has to. That's why we have to calculate thelitracy rate
of the particulars.
- In the dataset Male, Female and Literate columns are present instead of Literacy Rate and Sex Ratio.
- The dataset is in wide formate so I turn it into long formate for analysis.
Created by arv-anshul
Used dataset is not appropiate for real life analysis. I just used it to improve my skills. Find the used datasets here.