Data Analytics Lab

LAB 1. IRIS Dataset Analysis

Download the Iris flower dataset or any other dataset into a DataFrame. (eg https://archive.ics.uci.edu/ml/datasets/Iris )
Use Python/R and Perform following-

How many features are there and what are their types (e.g., numeric, nominal)?

Compute and display summary statistics for each feature available in the dataset.

(eg. minimum value, maximum value, mean, range, standard deviation, variance and percentiles

Data Visualization-Create a histogram for each feature in the dataset to illustrate the feature distributions. Plot each histogram.

Create a boxplot for each feature in the dataset. All of the boxplots should be combined into a single plot. Compare distributions and identify outliers.

LAB 2. Pima Indians Diabetes Dataset Analysis (W.I.P)

Download Pima Indians Diabetes dataset. Use Naive Bayes‟ Algorithm for classification.

Load the data from CSV file and split it into training and test datasets.

summarize the properties in the training dataset so that we can calculate probabilities and make predictions.

Classify samples from a test dataset and a summarized training dataset.