It is important to be able to obtain relevant information from available weather data due to the impact of weather on military activities, such as traffic, health, usage and functionality of electronic equipment etc. Interpolation can be used to estimate values based on existing data. Using Lagrange's Interpolation, we can estimate the temperature recordings for every month in 2015 by interpolating the temperatures from 2011 to 2016. A comparison can be drawn between the estimated and actual values to note the accuracy.
- This repository contains the CSV file of the data and the Jupyter Notebook containing the code for drawing the analysis.
- Python libraries such as Pandas, Matplotlib, Numpy, Scipy, Numpy.Polynomial and Statistics have been used.
- Lagrange’s Interpolation was verified as the values were obtained within the range.
- The temperature recordings were quite accurate with only 0.5% to 6.4% error.
Medium Article: -
: https://medium.com/@jainshireen/temperature-estimation-using-lagranges-interpolation-fe011ae7131d
Dataset used for analysis: -
: https://www.kaggle.com/code/rajnaruka0698/indian-weather-analysis-and-forecast/data