由于两个df的格式/列名相同，因此您可以将它们命名为：

for i in df_iter_actuals.columns:
    plt.figure(figsize = (10,8))
    plt.plot(df_iter_actuals[i])
    plt.plot(df_iter_preds[i])
    plt.title(f'Pct Error of CPR Predictions for {i}')

# Create figure and axes
fig, ax = plt.subplots(figsize=(10, 8))

# Iterate over columns in dataframes
for col in df_iter_actuals.columns:
    # Use the `df.plot()` function to plot the column from each dataframe
    df_iter_actuals[col].plot(ax=ax, label="Actual")
    df_iter_preds[col].plot(ax=ax, label="Predicted")

    # Set the title of the plot to the column name to whatever you need
    ax.set_title(f"Pct Error of CPR Predictions for {col}")
    
    # Show the plot and legend
    ax.legend()
    plt.show()

只需迭代两个 Dataframe 的列，然后使用df.plot()函数将两个 Dataframe 的每列绘制在同一个图形上！

您可以使用concat和groupby.plot：

(pd.concat([df_iter_actuals, df_iter_preds], keys=['actual', 'pred'], axis=1)
   .groupby(level=1, axis=1).plot()
)