Data analysis using R and Python

R and Python can be used for data analysis. Below we shall be illustrating how one can use R or Python to do data analysis. The data files used for illustrative purposes are taken from various government resources. The data description file can be referred to know more about the data. The data files are provided in 3 formats namely, .csv, .xls and .xlsx formats. You can use any of these to start your practice.

This work is done under the guidance of Prof. Radhendushka Srivastava, Dept. of Mathematics, IIT Bombay.


Indian Agriculture Data - Documentation.pdf

Indian Agriculture Data.csv

Indian Agriculture Data.xls

Indian Agriculture Data.xlsx

The sample lab migration code given here is a step by step guide to use R for data analysis. It is helpful not only to those who are beginners in R but also to those who are already using proprietary software for data analysis.

  1. Module-1: Setting Working Directory in R
  2. Module-2: Reading Data Files in R
  3. Module-3: Extracting a Column
  4. Module-4: Creating a Frequency Table
  5. Module-5: Creating a Bar Chart
  6. Module-6: Creating a Pie Chart
  7. Module-7: Summary Statistics of a Continuous Variable
  8. Module-8: Creating a Histogram

The sample lab migration code given here is a step by step guide to use Python for data analysis.

  1. Module-0: Anaconda Navigator
  2. Module-1: Jupyter notebook
  3. Module-2: Setting Working Directory in Python
  4. Module-3: Reading Data Files in Python
  5. Module-4: Data Types in Python
  6. Module-5: Extracting a Column