Import all the libraries listed in the first cell. Make sure all modules are installed. Use the data set provided to answer the following: 6. a) What is the lowest price for Safaricom (SCOM) b) What was the date when Safaricom had the lowest price? 7. a) What is the highest price Safaricom stock reached in the data b) What was the date when Safaricom stock recorded the highest price? 8. Create a line plot for Safaricom stock and verify if the information provided above is indeed correct. 9. Select one of the sectors provided (agric, comm, bank, const, energy, insur, invest, manu) 10. a) Use pandas to create a subset containing all the rows of the dataframe and only companies in your selected sector. Rename this dataframe to the sector_name_df 11. b) Using the subset for the sector, use matplotlib subplot to create subplots to fit all the sector stocks in one plot. One row can have a maximum of 3 charts. 12. c) Using your sector DataFrame use the corr() DataFrame method to come up with a correlogram. Create a DataFrame for these correlations 13. d) Use Seaborn to plot the correlation plot for your sector stocks. Key performance Metrics: • Go an extra step to produce charts that are visually appealing • Ensure all the plots have a Title • Ensure all plots have x labels and y labels where applicable • Your plots should be clearly visible. Change the size of your plot to a comfortable width and height. • Save all your plots