India GDP & population analysis

GDP & POPULATION ANALYSIS OF INDIAN STATES USING PYTHON LIBRARIES

INTRO

Through this project I have analyzed the GDP and population data of various states of India for the period of 1990 to 2021. I chose to focus on analyzing parameters such as gross state domestic product, per capita income, and net state domestic product as these are key indicators of a state's economic performance and can provide insights into the standard of living of its residents and see how the country has performed over the years.

DATA PREP

Analysis was conducted by loading the data from 2 separate excel files containing the GDP and population of the various states in India and performed data cleaning, manipulation, and visualization using python libraries such as Pandas, Matplotlib, Seaborn, and Plotly.

Next step involves cleaning and manipulating the data. I selected the columns containing the years from the GDP data, and then used Pandas melt function to convert the data into a long format. I also filled in any missing values in the 'value' column with 0 and converts the data type of this column to integer.
I then created dummy variables for the 'CATEGORY' column and assigns the value of the 'value' column to the corresponding dummy variable and performed a similar cleaning process for the population data, filling in missing values, and creating dummy variables.
After cleaning the data, I grouped the data by state and year, and calculated the sum of numerical values for each group.
I then selected the data for the year 2021 and merged the GDP and population data for this year based on the 'state' column.
I then defined a function named 'get_top_per_capita_states' that takes a state name and a dataframe as input and returns the top five states with the highest NSDP and Per Capita Income, including the input state.
This function was later used to create a bar plot using the Plotly graph_objects library to visualize the NSDP percentage and Per Capita NSDP for the top five states.

ANALYSIS

India's Gross State Domestic Product (GSDP) and Net State Domestic Product (NSDP) have shown a steady increase from 1990 to 2021.
Between 2011 and 2012, there was a huge increase in both GSDP and NSDP, almost doubling in size.
This increase was likely due to a combination of factors, including a growing population, increased investment and infrastructure spending, and policy reforms aimed at promoting economic growth.
However, between 2020 and 2021, there was a drop in both GSDP and NSDP, likely due to the economic impact of the COVID-19 pandemic, which led to disruptions in supply chains, decreased consumer demand, and reduced investment.
The pandemic also led to widespread job losses and income inequality, which likely contributed to the decline in GSDP and NSDP.

The scatter plot shows the correlation among population, per capita income, and NSDP for various states in India. Here are the key observations:
- The smallest circle on the plot represents the state of Lakshadweep, which has a small population of only 66k and zero NSDP, GSDP, and per capita income. This suggests that the state's economy is underdeveloped and lacks resources.
- The largest circle on the top center of the graph represents the state of Maharashtra, which has a much larger population of 124.904K and high NSDP, GSDP, and per capita income. This indicates that Maharashtra is one of the most economically developed states in India.
- Delhi, with a population of 19,301K, has a circle that is closer to the origin compared to Maharashtra. Although Delhi's NSDP and GSDP are lower than Maharashtra's, the per capita income in Delhi is higher, indicating that the state has a more prosperous population.
- Karnataka has a population of 69.6K and relatively high NSDP, GSDP, and per capita income. This suggests that Karnataka has a developed economy with a high standard of living.
  Overall, the scatter plot highlights the varying levels of economic development and prosperity among different states in India, with some states like Maharashtra and Delhi having more developed economies and higher per capita incomes than others.

The graph shows the distribution of NSDP percentage across different states of India. The NSDP percentage represents the contribution of each state to India's overall NSDP:
- Maharashtra, with the highest NSDP percentage of 13.38%, has a strong and diverse economy, driven by industries such as manufacturing, finance, and services.
- Gujarat, the second highest, is a major industrial hub with a well-developed infrastructure and favorable business climate.
- Tamil Nadu, with an NSDP percentage of 8.86%, is also a significant industrial and manufacturing center, particularly in the automobile and textile sectors.
- Karnataka, with 8.3%, has a diverse economy, including IT, biotech, and aerospace sectors.
- On the other hand, the states of Arunachal Pradesh and Jammu & Kashmir have the lowest NSDP percentages of 0.13% and 0.7% respectively.
- This could be due to several factors, such as the difficult terrain and lack of infrastructure in Arunachal Pradesh, and the ongoing conflict and instability in Jammu & Kashmir. These factors may limit the states' ability to attract investments and develop their economies.

GDP & POPULATION ANALYSIS OF INDIAN STATES USING PYTHON LIBRARIES

INTRO

DATA PREP

ANALYSIS

India's Gross State Domestic Product (GSDP) and Net State Domestic Product (NSDP) have shown a steady increase from 1990 to 2021.

Between 2011 and 2012, there was a huge increase in both GSDP and NSDP, almost doubling in size.

This increase was likely due to a combination of factors, including a growing population, increased investment and infrastructure spending, and policy reforms aimed at promoting economic growth.

However, between 2020 and 2021, there was a drop in both GSDP and NSDP, likely due to the economic impact of the COVID-19 pandemic, which led to disruptions in supply chains, decreased consumer demand, and reduced investment.

The pandemic also led to widespread job losses and income inequality, which likely contributed to the decline in GSDP and NSDP.

The scatter plot shows the correlation among population, per capita income, and NSDP for various states in India. Here are the key observations:

The smallest circle on the plot represents the state of Lakshadweep, which has a small population of only 66k and zero NSDP, GSDP, and per capita income. This suggests that the state's economy is underdeveloped and lacks resources.

The largest circle on the top center of the graph represents the state of Maharashtra, which has a much larger population of 124.904K and high NSDP, GSDP, and per capita income. This indicates that Maharashtra is one of the most economically developed states in India.

Delhi, with a population of 19,301K, has a circle that is closer to the origin compared to Maharashtra. Although Delhi's NSDP and GSDP are lower than Maharashtra's, the per capita income in Delhi is higher, indicating that the state has a more prosperous population.

The graph shows the distribution of NSDP percentage across different states of India. The NSDP percentage represents the contribution of each state to India's overall NSDP:

Maharashtra, with the highest NSDP percentage of 13.38%, has a strong and diverse economy, driven by industries such as manufacturing, finance, and services.

Gujarat, the second highest, is a major industrial hub with a well-developed infrastructure and favorable business climate.

Tamil Nadu, with an NSDP percentage of 8.86%, is also a significant industrial and manufacturing center, particularly in the automobile and textile sectors.

Karnataka, with 8.3%, has a diverse economy, including IT, biotech, and aerospace sectors.

On the other hand, the states of Arunachal Pradesh and Jammu & Kashmir have the lowest NSDP percentages of 0.13% and 0.7% respectively.

This could be due to several factors, such as the difficult terrain and lack of infrastructure in Arunachal Pradesh, and the ongoing conflict and instability in Jammu & Kashmir. These factors may limit the states' ability to attract investments and develop their economies.