project_part_2.py

"""
This module contains the code required to operate the second part of the project
"""
import matplotlib.pyplot as plot
import pandas as p
from matplotlib.figure import Figure
import project_part_1 as proj1


industries_and_indexes = proj1.industry_and_its_index  # The dictionary corresponding to the industries

pre_pandemic_data = p.read_csv('Datasets/pre_pandemic.csv')
during_the_pandemic_data = p.read_csv('Datasets/during_the_pandemic (1).csv')
# (Change the input string if the file names or the folder names are different.)


def create_dataframe(industry: str, time_frame: str) -> p.DataFrame:
    """
    Create and return a new pandas dataframe

    Preconditions:
        - timeframe in ["January 2019- 20", "February 2019- 20", "March 2019- 20",
                "April 2019- 20", "May 2019- 20", "June 2019- 20",
               "July 2019- 20", "August 2019- 20", "September 2019-r 2019- 2 20",
                "October 2019- 20", "November 2019- 20", "Decemebe0"]

        - industry in proj1.industry_and_its_index
    """
    # Creating a new DataFrame where rows and columns are 0-indexed by default
    new_dataframe = p.DataFrame(columns=["Industry", "Time Frame", "Pre-Pandemic Value", "Value During the Pandemic",
                                         "Increase- Decrease", "Percentage of Increase - Decrease"], index=["values"])

    industry_name = industry.split(' ')
    industry_name_fixed = [industry_name[0]]
    # Accumulator for the new industry name so that the first alphabet of each word is capitalized,
    # index 0 doesn't count because its first letter is capitalized by default.

    for i in range(1, len(industry_name)):
        if industry_name[i][0].islower() and industry_name[i] != 'and':
            industry_name_fixed.append(industry_name[i].replace(industry_name[i][0],
                                                                industry_name[i][0].capitalize(), 1))
        else:
            industry_name_fixed.append(industry_name[i])

    # If the first alphabet of the word is lower cased then change it to upper case,
    # the first word of the industry should always have an uppercase letter

    if len(industry) > 30:
        industry_name_fixed.insert(len(industry_name) // 2, '\n')

    new_industry_name = ' '.join(industry_name_fixed)

    new_dataframe["Industry"] = new_industry_name

    dates_to_indexes = {"January 2019- 20": 0, "February 2019- 20": 1,
                        "March 2019- 20": 2, "April 2019- 20": 3,
                        "May 2019- 20": 4, "June 2019- 20": 5,
                        "July 2019- 20": 6, "August 2019- 20": 7,
                        "September 2019- 20": 8, "October 2019- 20": 9,
                        "November 2019- 20": 10, "Decemeber 2019- 20": 11}

    dates = list(dates_to_indexes.keys())

    # The iloc[:, :] function allows us to access specific values from the DataFrame by their indexes.

    # The first parameter, which is the rows,  takes 2 integers separated by a colon (:)
    # and gives out that part of the data frame. The end point is exclusive.

    # The second parameter, which is the colums,  takes 2 integers separated by a colon (:)
    # and gives out that part of the data frame. The end point is exclusive.

    # For example iloc[4 : 7, 3 : 14] would return the rows 4, 5 and 6; the columns from 3 up to but not including 14.

    new_dataframe["Time Frame"] = dates[dates_to_indexes[time_frame]]  # Modifying the "timeframe" column

    value_1 = during_the_pandemic_data.iloc[industries_and_indexes[industry], dates_to_indexes[time_frame] + 1]
    # Getting the necessary value from during_the_pandemic_data
    value_2 = pre_pandemic_data.iloc[industries_and_indexes[industry], dates_to_indexes[time_frame] + 1]
    # Getting the necessary value from pre_pandemic_data

    new_dataframe["Pre-Pandemic Value"] = value_2
    new_dataframe["Value During the Pandemic"] = value_1

    differences = round(value_1 - value_2, 2)

    new_dataframe["Increase- Decrease"] = differences

    different_percentage = str(round(100 * ((value_1 - value_2) / value_2), 2)) + '%'
    new_dataframe["Percentage of Increase - Decrease"] = different_percentage
    # Getting a percentage

    return new_dataframe


def create_table_value(df: p.DataFrame) -> list[tuple[str, float]]:
    """Returns the value of a DataFrame into a list of tuples

    >>> values = create_dataframe('Agriculture', 'January 2019- 20')
    >>> create_table_value(values)
    [('Industry', 'Agriculture'),\
 ('Time Frame', 'January 2019- 20'),\
 ('Pre-Pandemic Value', 40.2),\
 ('Value During the Pandemic', 38.9),\
 ('Increase- Decrease', -1.3),\
 ('Percentage of Increase - Decrease', '-3.23%')]


    """
    df_to_dict = df.to_dict()

    data_list = []
    for item in df_to_dict:
        data_list.append((item, df_to_dict[item]['values']))

    return data_list


def create_table(industry: str, time_frame: str) -> Figure:
    """Creates the table with the data

    >>> create_table('Agriculture', 'January 2019- 20')
    <Figure size 1600x1200 with 1 Axes>
    """

    data = create_table_value(create_dataframe(industry, time_frame))
    values = [data[i][0] for i in range(len(data))]
    numerics = [str(data[i][1]) for i in range(len(data))]

    figure, tables = plot.subplots(facecolor='#73C2FB')
    tables.set_axis_off()
    table = tables.table(
        cellText=[numerics],
        rowLabels=None,
        colLabels=values,
        loc='upper center'
    )
    table.auto_set_font_size(False)
    table.set_fontsize(10)
    table.scale(1.25, 1.5)
    figure.set_size_inches(16, 12)

    tables.set_title('Difference in Percentage Pre and During Pandemic')

    plot.box(on=None)

    return figure


if __name__ == '__main__':
    import doctest
    doctest.testmod()

    import python_ta
    import python_ta.contracts
    python_ta.contracts.DEBUG_CONTRACTS = False
    python_ta.contracts.check_all_contracts()
    python_ta.check_all(config={
        'extra-imports': ['python_ta.contracts', 'pandas', 'matplotlib.pyplot', 'project_part_1',
                        'matplotlib.figure'],
        'max-line-length': 121,
        'max-nested-blocks': 4,
        'disable': ['R1705', 'C0200']
    }
    )