【数据分析&数据挖掘】2000-2017年各个产业、行业的柱状图

import matplotlib.pyplot as plt
import numpy as np

def draw_data(n, a, b, c, d, values, fig, plt, t, xl, ticks):
    fig.add_subplot(2, 2, n)
    x = np.arange(1, c, 1)
    y = values[d, a:b+1]
    print("---y---:
",y)
    plt.bar(x, y, width=0.5, color=["#BCEE68", "#A2CD5A", "#6E8B3D"])
    plt.title(t)
    plt.xlabel(xl)
    plt.ylabel("生产总值（亿元）")
    plt.xticks(x, ticks)
    for i,j in zip(x, y):
        plt.text(i, j, "%.2f亿元"%j, horizontalalignment='center', verticalalignment='bottom')
    return plt

def show_data():
    fig = plt.figure(figsize=(20, 12), dpi=120)
    plt.rcParams['font.sans-serif'] = 'SimHei'
    plt.rcParams['axes.unicode_minus'] = False
    # plt.subplots_adjust(hspace=0.3)
    return fig, plt

def save_data():
    plt.savefig("./2000-2017年各个产业、行业的柱状图.png")
    plt.show()
    return None


def build_data():
    res = np.load("./国民经济核算季度数据.npz", allow_pickle=True)
    columns = res["columns"]
    values = res["values"]
    # print(columns)
    # print(values)
    return columns, values

def main():
    columns, values = build_data()
    fig, plt = show_data()
    title1 = "2000年第一季度国民总值产业构成分布柱状图"
    title2 = "2017年第一季度国民总值产业构成分布柱状图"
    xlabel1 = "产业"
    xlabel2 = "行业"
    ticks1 = [tmp[:4] for tmp in columns[3:6]]
    ticks2 = [tmp[:2] for tmp in columns[6:]]
    draw_data(1, 3, 5, 4, 0, values, fig, plt, title1, xlabel1, ticks1)
    draw_data(2, 3, 5, 4, 68, values, fig, plt, title2, xlabel1, ticks1)
    draw_data(3, 6, 14, 10, 0, values, fig, plt, title1, xlabel2, ticks2)
    draw_data(4, 6, 14, 10, 68, values, fig, plt, title2, xlabel2, ticks2)
    save_data()


if __name__ == '__main__':
    main()