DigestSquare

Hypothesis to be tested : The Digits data set of scikit-learn library provides numerous data-sets that are useful for testing many problems of data analysis and prediction of the results. Some Scientist claims that it predicts the digit accurately 95% of the times. Perform data Analysis to accept or reject this Hypothesis. I took the handwritten letter dataset from  Digit Recognizer | Kaggle  .    Each image is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total. Each pixel has a single pixel-value associated with it, indicating the lightness or darkness of that pixel, with higher numbers meaning darker. This pixel-value is an integer between 0 and 255, inclusive. The training data set, (train.csv), has 785 columns. The first column, called "label", is the digit that was drawn by the user. The rest of the columns contain the pixel-values of the associated image. command :- data.info() <class 'pandas.core.frame.DataFrame'> RangeIndex: ...

The process of data analysis actually begins long before the collection of raw data. For the analysis purpose I extracted data from  https://www.kaggle.com/muthuj7/weather-dataset   . The dataset has hourly temperature recorded for last 10 years starting from 2006-04-01 00:00:00.000 +0200 to 2016-09-09 23:00:00.000 +0200. It corresponds to Finland, a country in the Northern Europe. The data set contains 12 features which can be explored. The goal of this data analysis is to transform the raw data into information and then convert it into knowledge. For this I made use of Available python libraries  Pandas, scikit-learn , matplotlib. Finally I want to put-forth my conclusion below The total number of rows and columns are (96453, 12). where 12 features of weather is observed over 96,453 days. Features 1. Formatted date 2. Summary 3.Precipitation Type 4.Temperature (C) 5.Apparent Temperature (C) [ apparent temperature tells you how warm or cool your body thinks ...