Project Python: Data Analysis

Expectations: Understand the code demonstrated in the video tutorials, slightly modify the code to accomplish tasks below. Remember, you will not be able to accomplish some of the tasks if you do not understand what each line of the code does.

Download zip files and extract!! Work with files in the separate extracted folders!

Tasks:

$1.$ Work on LinkedIn Learning video tutorial Python Data AnalysisLinks to an external site.. Complete the sections: $"4.$ Arrays with NumPy", and $"5.$ Use Case: Weather Data". Create a Word file and save it as M$7\_$FL where FL are your First and Last name initials.

$2.$ Save your ipython notebook from working on the Section $5\mathrm{.}5$ Weather Charts as Weather$\_$Charts and this file should have a $.$ipynb extension name $(5$ points$).$ Next, modify the code so that your own name can be included in the last New York plot's title. Make a screenshot of the modified code $($not shown in the sample below$)$ and the plot that you created, save the screenshot in M$7\_$FL$.(5$ points$).$

Screenshot of temperature analysis with student name as sample output

Then write your own code in Weather$\_$Charts to plot a chart for 'DALLAS FT WORTH AP$\text{'}$ in year of $2020.$ Make a screenshot of the your code $($not shown in the sample below$)$ and the plot that you created, save the screenshot in M$7\_$FL $(5$ points$).$ The average temperature in your plot might show a different value because my plot was created on a different day from your plot.

Screenshot of Dallas FT Worth temperature analysis sample output

$3.$ The Section $5$: Challenge is answered in the tutorial but I want you to think and try to solve the problem before looking at the Solution. Use the solution to help understanding how the problem is solved. Save your ipython notebook from working on the Section $5$: Challenge as Weather$\_$Anomalies and this file should have a $.$ipynb extension name $(5$ points$).$

Modify the code to include 'DALLAS FT WORTH AP$\text{'}$ in the last plot. Make a screenshot of the code $($not shown in the sample below$)$ and the plot that you created, save the screenshot in M$7\_$FL $(5$ points$).$Screenshot of temperature anomaly sample output with Dallas FT Worth Data included

When you look at this chart, you can see that much of the data is missing for cities like Minneapolis before $1950$ and could not be displayed. Therefore, you need to add new code to "compute and plot the temperature anomaly time series for any station" between $1950-2020.$ In this task, the temperature anomaly is defined very similar to the Challenge, but the years average temperature is now in the range of year $1950-2020($not challenge's $1880-2020),$ and the "midcentury average" should be $($TMIN $+$ TMAX$)/2$ averaged over all days of every year between $1980$ and $1990($not challenge's $1945-1955,$ because we are looking at range of $1950-2020$ and 'midcentury' in this range is $1980-1990).$ Add a title to the plot to include your own name.

Make a screenshot of the code $($not shown in the sample below$)$ and the plot that you created for New York, Minneapolis, and Dallas Ft Worth AP$.(20$ points$)$ Write your analysis of the temperature anomaly observed in this plot in the M$7\_$FL document $(5$ points$).$

Screenshot of temperature anomaly sample output

$4.$ Work on LinkedIn Learning video tutorial Python Data AnalysisLinks to an external site.. Complete the sections: $"6.$ pandas", and $"7.$ Use Case: Baby Names". Save your ipython notebook from working on the Section $7\mathrm{.}3$ "Comparing name popularity" as Name$\_$Popularity and this file should have a $.$ipynb extension name $(5$ points$).$ Next, add your own code to compare the popularity of your own name and one of your relatives. Also add a title to the plot as shown the following screenshot. In my example, my name is "Jane", my relative's name is "Frances". Make a screenshot of the modified code $($not shown in the sample below$)$ and the plot that you created, save the screenshot in M$7\_$FL$.(10$ points$).$ Write your analysis of the names' popularity shown in your plot in the M$7\_$FL document $(5$ points$).$

If your name or family member's name is not in the data set, use "Penny" as a female name and "Ken" as a male name depending on your own case.

Screenshot of name popularity project sample result

$5.$ The Section $7$: Challenge is answered in the tutorial but I want you to think and try to solve the problem before looking at the Solution. Use the solution to help understanding how the problem is solved. Save your Jupyter notebook from working on the Section $7$: Challenge as Pandas$\_$Names and this file should have a $.$ipynb extension name $(5$ points$).$ In the Pandas$\_$Names notebook, write your own code to plot your own name and at least one relative's name in the male and female name popularity. In the following example, I plot my name "Jane" and a relative's name "John" in the male and female name popularity. We can see John is used as male name dominantly. Take a screenshot of the code $($not shown in the sample below$)$ and the plot your creat