如何对python中的x轴标签和传说进行排序？

Question

排序X轴标签

我有一个python包含的字典列表，我正在整理和排序使用熊猫数据在宽形式。我希望在图形中看到的是，x轴标签将按年份和周期进行分组和排序。这里的周期可能在1-52之间。但我看到的是其中一个组没有被分类(或者没有完全排序)。我试着更新categoryorder 文档。似乎不像我预料的那样起作用了。这是我希望看到的x轴标签上的一个组的顺序：

T311-PM2:2019-8, T311-PM2:2019-11, T311-PM2:2019-12, T311-PM2:2020-3.

排序传说

传说中也有类似的行为。我尝试使用legend_traceorder 文档进行排序。

我希望看到这样的订单：

CS1 P, CS1-1 P, CS2 P, CS3 P, CS4 C, CS5 R, CS6 P, CS7-1 C, CS7-2 S, CS8 P

这是我将在代码中使用的dict数据：

response_dict = {
    "data": [
        {
            "machineType": "L10-Alpha1-PM4",
            "date": "2021-1",
            "event": "CS3 P",
            "mins": "0.00"
        },
        {
            "machineType": "L10-Alpha1-PM4",
            "date": "2021-1",
            "event": "CS7-2 S",
            "mins": "7.14"
        },
        {
            "machineType": "L10-Alpha1-PM4",
            "date": "2021-1",
            "event": "CS8 P",
            "mins": "4.17"
        },
        {
            "machineType": "T311-PM2",
            "date": "2019-8",
            "event": "CS1 P",
            "mins": "21.14"
        },
        {
            "machineType": "T311-PM2",
            "date": "2019-11",
            "event": "CS4 C",
            "mins": "2.92"
        },
        {
            "machineType": "T311-PM2",
            "date": "2019-11",
            "event": "CS5 R",
            "mins": "327.88"
        },
        {
            "machineType": "T311-PM2",
            "date": "2019-12",
            "event": "CS7-1 C",
            "mins": "43.90"
        },
        {
            "machineType": "T311-PM2",
            "date": "2019-12",
            "event": "CS6 P",
            "mins": "2147.27"
        },
        {
            "machineType": "T311-PM2",
            "date": "2019-8",
            "event": "CS8 P",
            "mins": "0.10"
        },
        {
            "machineType": "T311-PM2",
            "date": "2020-3",
            "event": "CS8 P",
            "mins": "19.31"
        },
        {
            "machineType": "T828-PM2",
            "date": "2018-5",
            "event": "CS1-1 P",
            "mins": "11.43"
        },
        {
            "machineType": "T828-PM2",
            "date": "2018-5",
            "event": "CS2 P",
            "mins": "10.83"
        }
    ]
}

我的代码

import pandas as pd
import plotly.express as px

df_normalized = pd.json_normalize(response_dict['data'])
df_normalized['Mission'] = df_normalized[['machineType', 'date']].agg(':'.join, axis=1)
df_normalized[['year', 'period']] = df_normalized['date'].str.split('-', expand=True).astype(int)
data_frame = df_normalized.sort_values(by=['year', 'period'])
figure = px.bar(data_frame, x='Mission', y='date', color='event').update_xaxes(categoryorder='category ascending')#.update_layout(legend_traceorder='normal')
figure.show()

图

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Answer 1

您的方向是正确的，只需要使用category_orders而不是categoryorder，并使用sorted()方法定义数据的顺序。

df_normalized = pd.json_normalize(response_dict['data'])
df_normalized['Mission'] = df_normalized[['machineType', 'date']].agg(':'.join, axis=1)
df_normalized[['year', 'period']] = df_normalized['date'].str.split('-', expand=True).astype(int)
data_frame = df_normalized.sort_values(by=['year', 'period']).reset_index(drop=True)
figure = px.bar(data_frame, x='Mission',y='date', color='event',\
                category_orders={'event':sorted(data_frame.event.unique()),\
                                 'Mission':sorted(data_frame.Mission,\
                                                  key = lambda x: pd.to_datetime(x.split(':')[1]))})
figure.show()

P.S:我通常在.reset_index(drop=True)上使用.sort_values()之后的DataFrame，以保持索引值的正确顺序。

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