# **Day-01:** Apply the Housing Dataset provided to explore Python frameworks - NumPy, Pandas, Matplotlib, Seaborn, Numpy, 

**Task 1:**  a. Create a Numpy array from the list,  apply Sin, Cos special functions
b. Perform matrix multiplication of the Array's created and display the matrix 
c. Generate three 2-D arrays and perform Addition, Subtraction, Multiplication, and transposition. 
 of array
d. Indexing and slicing of elements of the array
e. Conditional subsetting of lists based on random index selected.


**Task 2: **Implement using Pandas Library the following tasks:
a. create a data frame from the dataset and display the dataset columns.
b. Verify the data type of the DataFrame
c. Perform Descriptive stats on the DataFrame dataset 
d. Indexing, slicing, conditional subsetting of columns in the dataset
e. Perform arithmetic operations on specific rows/columns - sum, max, min, std, 
**f. Compute the Root Mean Square Error for the dataset (mandatory)**

**Task 3:** Visualize the Dataset provided using Python Matplotlib and Seaborn 
a.scatterplot,
b.boxplot,
c.histogram,
d.violin plot,
e.bar charts,
f.heatmap
g.time series
h. line plot

# Output Submission: upload the file generated using  ** output.to_csv("submission.csv", index=False)**

**Data Set:  Housing.csv**