7143CEM Assignment Help
Programming for Data Science Assignment help
(1) “Time series” data is a sequence of data points in time order, usually at equally spaced points in time. Find an interesting univariate (one variable) time series dataset from the Office for National Statistics (ONS) Time Series Explorer (https://www.ons.gov.uk/timeseriestool). Build one polished plot of your time series dataset using Python. Also use Python to illustrate one time series analysis concept such as rolling average, exponential smoothing or finite differences using your time series dataset. The only Python libraries you may use in this part are numpy and matplotlib, except that you may use pandas only to load the dataset and convert the relevant column to a numpy array using pandas.Series.to_numpy(). Please provide both Python code and any plots produced. Clearly indicate exactly where the dataset comes from.
(2) Find an existing graphical plot of a dataset in an article on the BBC News website, e.g., by searching Google Images for “bbc news graph”. Reproduce the graphical plot as closely as you can using any two of the seaborn, plotly and plotnine Python plotting libraries separately (but with some help from matplotlib). Comment on how well you are able to achieve this. Focus on the content of the plot rather than the exact look and aim to make the two plots as similar as possible. Include the original BBC News image, together with a weblink to the article it is in. Please provide both your Python code and the plots produced. You must clearly reference any sources you have used. The graphical plot you select must not consist only of text and must not be a pie chart.
(3) Use your experience from parts (1) and (2) to critically assess the Python plotting libraries you have used in terms of the following criteria: difficulty of coding, adaptability of the code, level of control over the plot layout or labelling, and quality of the graphical plot produced. Present your assessment in an appropriate table.