Exercises

1. In this exercise, we will be using Temperature_data.csv. This dataset has some missing values. Do the following:

   a) After reading the file into a pandas DataFrame, check whether the dataset is level I clean, and if not, clean it. Also, describe the cleanings (if any).

   b) Check whether the dataset is level II clean, and if not, clean it. Also, describe the cleanings (if any).

   c) The dataset has missing values. See how many, and run a diagnosis to see which types of missing values they are.

   d) Are there any outliers in the dataset?

   e) How should we best deal with missing values if our goal is to draw multiple boxplots that show the central tendency and variation of temperature across the months? Draw the described visualization after dealing with the missing values.

2. In this exercise, we are going to use the Iris_wMV.csv file. The Iris dataset includes 50 samples of 3 types of iris flowers, totaling 150 rows of data. Each flower is described by its sepal and petal length...