第一季度資料

"""
    明確任務：比較共享單車每個季度的平均騎行時間
"""
import os
import numpy as np
import matplotlib.pyplot as plt

data_path = r'D:\mycode\minidata\bikeshare'
data_filenames = ['2017-q1_trip_history_data.csv', '2017-q2_trip_history_data.csv',
                  '2017-q3_trip_history_data.csv', '2017-q4_trip_history_data.csv']


def collect_data():
    """
        Step 1: 資料收集
    """
    data_arr_list = []
    for data_filename in data_filenames:
        data_file = os.path.join(data_path, data_filename)
        data_arr = np.loadtxt(data_file, delimiter=',', dtype='str', skiprows=1)
        data_arr_list.append(data_arr)
    return data_arr_list


def process_data(data_arr_list):
    """
        Step 2: 資料處理
    """
    duration_in_min_list = []

    for data_arr in data_arr_list:
        duration_str_col = data_arr[:, 0]
        # 去掉雙引號
        duration_in_ms = np.core.defchararray.replace(duration_str_col, '"', '')

        # 型別轉換
        duration_in_min = duration_in_ms.astype('float') / 1000 / 60

        duration_in_min_list.append(duration_in_min)

    return duration_in_min_list


def analyze_data(data_arr_list):
    """
        Step 3: 資料分析
    """
    duration_mean_list = []

    for i, duration in enumerate(data_arr_list):
        duration_mean = np.mean(duration)
        print('第{}季度的平均騎行時間：{:.2f}分鐘'.format(i + 1, duration_mean))
        duration_mean_list.append(duration_mean)

    return duration_mean_list


def show_results(duration_mean_list):
    """
        Step 4: 結果展示
    """
    plt.figure()
    plt.bar(range(len(duration_mean_list)), duration_mean_list)
    plt.show()


def main():
    """
        主函式
    """
    # 資料獲取
    data_arr_list = collect_data()

    # 資料處理
    duration_ist = process_data(data_arr_list)

    # 資料分析
    duration_mean_list = analyze_data(duration_ist)

    # 結果展示
    show_results(duration_mean_list)


if __name__ == '__main__':
    main()