生成python按图分组的条形图时间序列

Question

我正在尝试从分组的 df 中生成一个绘图条形图。我有 groupby python 语句排序的数据。数据排列得当，但我无法生成绘图条形图。

python 给出一个值错误 ValueError：“x”的值不是“data_frame”中列的名称。应为 ['amount'] 之一，但收到：Issued_Date

此外，我希望条形图可以堆叠。例如，第 0 行和第 5 行是相同的日期，所以我想要堆叠条形

df_A = df_pre.groupby(['Transaction','Type'])["amount"].resample('M').sum().to_frame('amount')

fig = px.bar(df_A, x='Issued_Date', y='amount', color='Type',
             title='Timeseries amount',
             barmode='group',
             height=600
            )

fig.show()

df_A.to_dict('split')
{'index': [('No', 'B', Timestamp('2019-03-31 00:00:00')),
  ('No', 'E', Timestamp('2018-10-31 00:00:00')),
  ('No', 'H', Timestamp('2019-07-31 00:00:00')),
  ('So', 'B', Timestamp('2018-12-31 00:00:00')),
  ('So', 'E', Timestamp('2018-12-31 00:00:00')),
  ('So', 'H', Timestamp('2019-03-31 00:00:00')),
  ('So', 'H', Timestamp('2019-05-31 00:00:00')),
  ('So', 'H', Timestamp('2019-06-30 00:00:00')),
  ('So', 'H', Timestamp('2019-07-31 00:00:00'))],
 'columns': ['amount'],
 'data': [[39.21],
  [64.49],
  [572.78],
  [13.46],
  [44.54],
  [13.96],
  [0.0],
  [46.76],
  [13.28]]}

Answer 1

我提到了official reference，看到你的问题适用于它。

import pandas as pd
import numpy as np
import io

data = '''
Transaction Type Issued_date Value
Div H 2020-2-9 84.5
Div H 2020-5-10 84.49
Div H 2020-6-7 78.13
Div I 2020-4-5 124.04
Div A 2020-2-9 40.65
Div A 2020-3-8 38.51
Div A 2020-11-12 39.99
Shell B 2020-9-16 -463.29
'''

df = pd.read_csv(io.StringIO(data), sep='\s+')

import plotly.express as px

fig = px.bar(df, x="Issued_date", y="Value", color="Type", title="Transaction", barmode='group', height=600)
fig.show()