具有多索引 pandas 数据框的条形图
Barplot with multi-index pandas dataframe
有没有办法绘制 'client_nr' 与 'Credit Total':
示例：
当前代码：
credit_clients.iloc[-1].plot.bar()
产生：
Example 2
感谢您的帮助。
- 已合成与您的数据框相似的数据
- 绘图很简单，只需要 select Client Total from index using
.loc[]
import numpy as np
import pandas as pd
# synthesize data
i = pd.MultiIndex.from_product([pd.date_range("1-jan-2018", freq="M", periods=6), range(10)], names=["yearmonth","client_nr"])
df = pd.DataFrame(index=i, data=np.random.uniform(1,10, len(i))).unstack()
df.columns = df.columns.droplevel(0)
df.loc["Client Total"] = df.sum(axis=0)
# plot it...
df.loc["Client Total"].plot(kind="bar")
数据
yearmonth
0
1
2
3
4
5
6
7
8
9
2018-01-31 00:00:00
8.48257
9.38166
9.14367
7.52485
8.25407
4.9672
8.28687
2.96698
9.37681
2.36876
2018-02-28 00:00:00
5.99324
8.72813
6.06575
4.19694
8.03992
2.22363
9.56064
8.23965
6.97355
5.8883
2018-03-31 00:00:00
8.85086
8.48972
9.11997
7.91605
6.38338
9.33158
7.26467
8.00862
8.38145
6.81128
2018-04-30 00:00:00
7.69246
5.17472
7.73813
2.75313
7.12725
9.86623
2.16481
8.15056
6.81378
9.01334
2018-05-31 00:00:00
6.05941
3.29547
7.05862
9.83301
4.51411
4.11672
7.53534
5.52747
8.34065
3.13277
2018-06-30 00:00:00
9.7033
9.36859
4.35592
4.4328
5.61218
1.13454
9.63189
3.44345
6.60661
4.43206
Client Total
46.7818
44.4383
43.4821
36.6568
39.9309
31.6399
44.4442
36.3367
46.4928
31.6465
情节
条形由 client_nr 着色 - 使用 plotly
import plotly.express as px
px.bar(df.loc["Client Total"].reset_index(), x="client_nr", y="Client Total", color="client_nr")
有没有办法绘制 'client_nr' 与 'Credit Total':
示例：
当前代码：
credit_clients.iloc[-1].plot.bar()
产生：
Example 2
感谢您的帮助。
- 已合成与您的数据框相似的数据
- 绘图很简单，只需要 select Client Total from index using
.loc[]
import numpy as np
import pandas as pd
# synthesize data
i = pd.MultiIndex.from_product([pd.date_range("1-jan-2018", freq="M", periods=6), range(10)], names=["yearmonth","client_nr"])
df = pd.DataFrame(index=i, data=np.random.uniform(1,10, len(i))).unstack()
df.columns = df.columns.droplevel(0)
df.loc["Client Total"] = df.sum(axis=0)
# plot it...
df.loc["Client Total"].plot(kind="bar")
数据
| yearmonth | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-01-31 00:00:00 | 8.48257 | 9.38166 | 9.14367 | 7.52485 | 8.25407 | 4.9672 | 8.28687 | 2.96698 | 9.37681 | 2.36876 |
| 2018-02-28 00:00:00 | 5.99324 | 8.72813 | 6.06575 | 4.19694 | 8.03992 | 2.22363 | 9.56064 | 8.23965 | 6.97355 | 5.8883 |
| 2018-03-31 00:00:00 | 8.85086 | 8.48972 | 9.11997 | 7.91605 | 6.38338 | 9.33158 | 7.26467 | 8.00862 | 8.38145 | 6.81128 |
| 2018-04-30 00:00:00 | 7.69246 | 5.17472 | 7.73813 | 2.75313 | 7.12725 | 9.86623 | 2.16481 | 8.15056 | 6.81378 | 9.01334 |
| 2018-05-31 00:00:00 | 6.05941 | 3.29547 | 7.05862 | 9.83301 | 4.51411 | 4.11672 | 7.53534 | 5.52747 | 8.34065 | 3.13277 |
| 2018-06-30 00:00:00 | 9.7033 | 9.36859 | 4.35592 | 4.4328 | 5.61218 | 1.13454 | 9.63189 | 3.44345 | 6.60661 | 4.43206 |
| Client Total | 46.7818 | 44.4383 | 43.4821 | 36.6568 | 39.9309 | 31.6399 | 44.4442 | 36.3367 | 46.4928 | 31.6465 |
情节
条形由 client_nr 着色 - 使用 plotly
import plotly.express as px
px.bar(df.loc["Client Total"].reset_index(), x="client_nr", y="Client Total", color="client_nr")