Matplotlib实战之百分比柱状图绘制详解

fp = "d:/share/A0A0A.csv"
df = pd.read_csv(fp)
df

data = df[(df["sj"] >= 2013) & 
        (df["sj"] <= 2021) & 
        (df["zb"].isin(["A0A0A03", 
                        "A0A0A04",
                        "A0A0A05",
                        "A0A0A06",
                        "A0A0A07"]))].copy()
data["年消耗总量"] = data.groupby("sj").value.transform("sum")
data["各类消耗量占比"] = data["value"] / data["年消耗总量"]
data.loc[:, ["sjCN", "zbCN", "各类消耗量占比"]].head(10)

import matplotlib.ticker as mticker
data = data.sort_values("sj")
data["各类消耗量占比"] = data["各类消耗量占比"]*100
with plt.style.context("seaborn-v0_8"):
    fig = plt.figure()
    ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
    years = data["sjCN"].drop_duplicates(keep="first").tolist()
    bar_data = {
        "蔬菜及菌类(%)": data[data["zb"] == "A0A0A03"]["各类消耗量占比"].tolist(),
        "肉类(%)": data[data["zb"] == "A0A0A04"]["各类消耗量占比"].tolist(),
        "禽类(%)": data[data["zb"] == "A0A0A05"]["各类消耗量占比"].tolist(),
        "水产品(%)": data[data["zb"] == "A0A0A06"]["各类消耗量占比"].tolist(),
        "蛋类(%)": data[data["zb"] == "A0A0A07"]["各类消耗量占比"].tolist(),
    }
    bottom = np.zeros(len(years))
    for key, vals in bar_data.items():
        ax.bar(years, vals, label=key, bottom=bottom)
        bottom += vals
    # 设置Y轴刻度的显示格式
    ax.set_ylim(0, 110)
    yticks = ax.get_yticks().tolist()
    ax.yaxis.set_major_locator(mticker.FixedLocator(yticks))
    ax.set_yticklabels(["{}%".format(x) for x in yticks])
    ax.set_title("全国居民主要粮食消耗情况")
    ax.legend(loc="upper left", ncol=5)