缺失值（NaN 值）与填充值的重叠图

Question

我有以下包含两列的 Panda DataFrame。第一列是包含缺失值（NaN 值）的原始值，第二列是缺失插补的结果，用于填充第一列中的 NaN 值。我如何在同一个图表中绘制这两列，以显示具有填充值的原始值，如下图所示：

Data=pd.DataFrame([[3.83092724,        np.nan],
   [       np.nan, 3.94103207],
   [       np.nan, 3.86621724],
   [3.48386179,        np.nan],
   [       np.nan, 3.7430167 ],
   [3.2382959 ,        np.nan],
   [3.9143139 ,        np.nan],
   [4.46676265,        np.nan],
   [       np.nan, 3.9340262 ],
   [3.650658  ,        np.nan],
   [       np.nan, 3.10590516],
   [4.19497691,        np.nan],
   [4.11873876,        np.nan],
   [4.15286075,        np.nan],
   [4.67441617,        np.nan],
   [4.50631534,        np.nan],
   [       np.nan, 4.01349688],
   [       np.nan, 3.48459778],
   [       np.nan, 3.83495488],
   [       np.nan, 3.10590516],
   [       np.nan, 4.09355884],
   [4.8433281 ,        np.nan],
   [       np.nan, 3.33450675],
   [4.86672126,        np.nan],
   [       np.nan, 3.2382959 ],
   [       np.nan, 3.48210011],
   [       np.nan, 3.00958811],
   [       np.nan, 3.05774663]], columns=['original', 'filled'])

Answer 1

您需要标记，否则如果您的单个原始值被缺失值包围，图表将毫无意义。
我们首先绘制原始值。然后，对于填充值，我们用原始值填充与现有填充值直接相邻的任何缺失值，以获得从该原始值到 next/preceding 填充值的虚线。最后，我们将这些修改后的填充值列绘制为虚线。

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df=pd.DataFrame([[3.83092724, np.nan],
   [       np.nan, 3.94103207],
   [       np.nan, 3.86621724],
   [3.48386179,        np.nan],
   [       np.nan, 3.7430167 ],
   [3.2382959 ,        np.nan],
   [3.9143139 ,        np.nan],
   [4.46676265,        np.nan],
   [       np.nan, 3.9340262 ],
   [3.650658  ,        np.nan],
   [       np.nan, 3.10590516],
   [4.19497691,        np.nan],
   [4.11873876,        np.nan],
   [4.15286075,        np.nan],
   [4.67441617,        np.nan],
   [4.50631534,        np.nan],
   [       np.nan, 4.01349688],
   [       np.nan, 3.48459778],
   [       np.nan, 3.83495488],
   [       np.nan, 3.10590516],
   [       np.nan, 4.09355884],
   [4.8433281 ,        np.nan],
   [       np.nan, 3.33450675],
   [4.86672126,        np.nan],
   [       np.nan, 3.2382959 ],
   [       np.nan, 3.48210011],
   [       np.nan, 3.00958811],
   [       np.nan, 3.05774663]], columns=['original', 'filled'])

_,ax = plt.subplots()
df.original.plot(marker='o', ax=ax)

m = (df.filled.isna()&df.filled.shift(1).notna()) | (df.filled.isna()&df.filled.shift(-1).notna())
df.filled.fillna(df.loc[m,'original']).plot(ls='--', ax=ax, color=ax.get_lines()[0].get_color())

以上是一般情况下的干净解决方案。如果原始值是用实心不透明线绘制的，而填充值的线宽不大于原始值，则可以简单地先绘制完全填充的填充值，然后在该线的顶部绘制原始值价值观：

df.filled.fillna(df.original).plot(ax=ax, color='blue', ls='--')
df.original.plot(marker='o', ax=ax, color='blue')

缺失值（NaN 值）与填充值的重叠图

overlap graph of missing values (NaN values) with filled values

matplotlib

nan

missing-data

pandas