Data Science Task using Python: The Boston data set comes from the real estate industry in Boston (US). The data has 506 rows and 14 columns. Read the Boston Housing Data from http://lib.stat.cmu.edu/datasets/boston or from the sklearn datasets using the following codes:

### To get the BOSTON data from sklearn datasets

from sklearn import datasets

boston= datasets.load_boston ()

####Now transform the data as a pandas's DATAFRAME

import pandas as pd

df = pd.DataFrame(boston.data ,columns = boston.feature_names)

df['price']=boston.target

Append the following five rows with your data frame. CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO B LSTAT Price 0.069 10 2.3 0 0.53 6.5 65.2 4.01 1 290 15 395 4.9 24.0 0.69+X 10+X 2.3+.X 0 0.5+.X 6.5+.X 65.2+.X 4.1+.X 1 290+X 15+X 395+X 4.9+.X 24.3+X 0.68+X 11+X 2.4+.X 0 0.6+.X 6.6+.X 65.1+.X 4.0+.X 1 291+X 13+X 390+X 4.2+.X 24.2+X 0.67+X 12+X 2.5+.X 0 0.4+.X 6.5+.X 65.3+.X 4.2+.X 1 292+X 14+X 392+X 4.3+.X 24.1+X 0.66+X 13+X 2.4+.X 0 0.7+.X 6.5+.X 65.4+.X 4.1+.X 1 293+X 16+X 391+X 4.4+.X 24.2+X 

X is the sample two digits of (e.g, 98) .X is the sample two digits of (e.g, 98) with a decimal point

Hints: If your DataFrame is df, then use the following codes to append the first two rows with the data frame.

# List of data series

datarowsSeries = [pd.Series([0.069,10,2.3,0,0.53,6.5,65.2,4.01,1,290,15,395,4.9,24],

index=df.columns ), pd.Series([0.069,11,2.3,0,0.6,6.6,65.3,4.2,1,290,15,395,4.9,24],

index=df.columns ) ]

# Pass the list of data series to the append() to add multiple rows

new_data = df.append(datarowsSeries , ignore_index=True)

Answer the following questions in details (step by step):

1. A description of the data: what it is and where it came from.

2. What questions /objectives you are addressing.

3. Data Cleaning, if required.

4. Construct suitable plots of the data.

5. Find the correlation between the median value of owner-occupied homes with other variables.

6. Conduct appropriate mean and proportion tests.

7. Fit a suitable model to predict the median value of owner-occupied homes in Boston.

8. A brief discussion of the results.

More details can be found here -> https://drive.google.com/file/d/1rRrPigVerROaR_vtGPl1R1cNH0ajUXx2/view?usp=sharing