问题

我有两个数据框，其中包含多列。我将df＃1绘制为堆叠条形图，并将df＃2叠加为线图。如果df＃1中的数据系列存在于df＃2中，我希望条形段和线的颜色相同，以便进行比较。在下面的例子中，我希望“FO”的颜色相同。

数据框：

df＃1

        FO     MI

Date
08-Jan-23 0.4925 0.0000
15-Jan-23 0.9075 0.0000
22-Jan-23 0.9750 0.0250
29-Jan-23 0.9625 0.0375
05-Feb-23 0.9825 0.0000

df＃2

       FO      AR

Jan-23 1.0 1.1
Feb-23 1.0 2.2

这是我的代码：

# 构建数据框列的并集，以便线条和条形系列可以具有相同的颜色，以便进行比较
df_Plot1 = vg.dc_dF_Groups[employee]
cols = df_Plot.columns.union(df_Plot1.columns)  

cmap = matplotlib.colormaps['Set1']
colors = dict(zip(cols, cmap.colors))

# 绘制员工的费用
df_Plot.iloc[0:plotFinish].reindex(columns=cols).plot.bar(ax=ax1, color=df_Plot.columns.map(colors), rot=45, legend=True, xlabel='Date', ylabel='Actuals', alpha=0.5, stacked=True)

# 绘制员工的组分配
df_Plot1.iloc[0:plotFinish].reindex(columns=cols).plot.line(ax=ax2, color=df_Plot1.columns.map(colors), ylabel='Allocation', legend=True, linewidth=3)
ax1.legend(title='Actuals', bbox_to_anchor=(1.05,1.0), loc='upper left', ncol=1)
ax2.legend(title='Allocations', bbox_to_anchor=(1.05,0.5), loc='upper left', ncol=1)
fig.suptitle(employee)

<details>
<summary>英文:</summary>

I have two data frames with several columns.  I plot df#1 as as stacked bar plot and overlay df #2 as a line plot.  If a data series in df#1 is present in df#2 I want the color of the bar segment &amp; line to be the same, for ease of comparison.  How would I do that?  Below, I would want the colors of &#39;FO&#39; to be the same.

Data Frames:

df#1

        FO     MI

Date
08-Jan-23 0.4925 0.0000
15-Jan-23 0.9075 0.0000
22-Jan-23 0.9750 0.0250
29-Jan-23 0.9625 0.0375
05-Feb-23 0.9825 0.0000

df#2

       FO      AR

Jan-23 1.0 1.1
Feb-23 1.0 2.2

Here's my code:

# Build a union of the dataframe columns so the line and bar series can have the same color
# for ease of comparison
df_Plot1 = vg.dc_dF_Groups[employee]
cols = df_Plot.columns.union(df_Plot1.columns)  

cmap = matplotlib.colormaps['Set1']
colors = dict(zip(cols, cmap.colors))

# Plot the employee's charges
df_Plot.iloc[0:plotFinish].reindex(columns=cols).plot.bar(ax=ax1, color=df_Plot.columns.map(colors), rot=45, legend=True, xlabel='Date', ylabel='Actuals', alpha=0.5, stacked=True)

# Plot the employee's group allocations
df_Plot1.iloc[0:plotFinish].reindex(columns=cols).plot.line(ax=ax2, color=df_Plot1.columns.map(colors), ylabel='Allocation', legend=True, linewidth=3)
ax1.legend(title='Actuals', bbox_to_anchor=(1.05,1.0), loc='upper left', ncol=1)
ax2.legend(title='Allocations', bbox_to_anchor=(1.05,0.5), loc='upper left', ncol=1)
fig.suptitle(employee)

</details>


# 答案1
**得分**: 1

你可以获得列的 [`union`](https://pandas.pydata.org/docs/reference/api/pandas.Index.union.html) 和 [`reindex`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.reindex.html)：

```python
cols = df1.columns.union(df2.columns)

fig, axes = plt.subplots(ncols=2)

df1.reindex(columns=cols).plot.bar(stacked=True, ax=axes[0])
df2.reindex(columns=cols).plot.line(ax=axes[1])

输出：

或者，创建一个自定义颜色列表，并从列名映射它们：

import matplotlib

cols = df1.columns.union(df2.columns)

cmap = matplotlib.colormaps['Set1']
colors = dict(zip(cols, cmap.colors))

fig, axes = plt.subplots(ncols=2)

df1.plot.bar(stacked=True, color=df1.columns.map(colors), ax=axes[0])
df2.plot.line(color=df2.columns.map(colors), ax=axes[1])

输出：

cols = df1.columns.union(df2.columns)

fig, axes = plt.subplots(ncols=2)

df1.reindex(columns=cols).plot.bar(stacked=True, ax=axes[0])
df2.reindex(columns=cols).plot.line(ax=axes[1])

import matplotlib

cols = df1.columns.union(df2.columns)

cmap = matplotlib.colormaps['Set1']
colors = dict(zip(cols, cmap.colors))

fig, axes = plt.subplots(ncols=2)

df1.plot.bar(stacked=True, color=df1.columns.map(colors), ax=axes[0])
df2.plot.line(color=df2.columns.map(colors), ax=axes[1])