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我有以下代码，它给了我非常奇怪的错误，我的目标是用不同的标签回填数据的缺失值。df_filled[is_filled]如果我更改一切正常但使用freq = 2D，则错误发生在这一行 df_filled=df.asfreq(freq='D').fillna(method='bfill', limit=1).dropna(how='all').drop_duplicates(keep='last')，df_filled [is_filled] 没有布尔形式。

    from datetime import datetime, timedelta
    import pandas as pd
    import numpy as np
    import random
    ##Generate the Data
    np.random.seed(11) 
    date_today = datetime.now()
    ndays = 15
    df = pd.DataFrame({'date': [date_today + timedelta(days=(abs(np.random.randn(1))*2)[0]*x) for x in range(ndays)], 
                       'test': pd.Series(np.random.randn(ndays)),     'test2':pd.Series(np.random.randn(ndays))})
    df1=pd.DataFrame({'date': [date_today + timedelta(hours=x) for x in range(ndays)], 
                       'test': pd.Series(np.random.randn(ndays)),     'test2':pd.Series(np.random.randn(ndays))})
    df2=pd.DataFrame({'date': [date_today + timedelta(days=x)-timedelta(seconds=100*x) for x in range(ndays)], 
                       'test': pd.Series(np.random.randn(ndays)),     'test2':pd.Series(np.random.randn(ndays))})
    df=df.append(df1)
    df=df.append(df2)
    df = df.set_index('date').sort_index()
    df = df.mask(np.random.random(df.shape) < .7)
    df=df.reset_index()
    df['test']=df['test'].astype(str)
    df['test2']=df['test2'].astype(str)
    df.replace('nan', np.nan, inplace = True)
    ##

    df.set_index(df['date'].dt.date, inplace = True) 

    df = df[~df.index.duplicated(keep='first')]
    df_filled=df.asfreq(freq='2D').fillna(method='bfill', limit=2).dropna(how='all').drop_duplicates(keep='last')
    df_filled.set_index(df_filled['date'],inplace=True)
    df_filled=df_filled.drop('date',1)
    df.set_index(df['date'],inplace=True)
    df=df.drop('date',1)
    is_filled = (df.isnull() & df_filled.notnull()) | df.notnull() 
    df_filled[is_filled] ## error happens here
    df_filled[is_filled]=df_filled[is_filled].applymap(lambda x: '_2D' if pd.notnull(x)  else np.nan)

输出： ValueError: Must pass DataFrame with boolean values only

我提前感谢您的帮助。

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1 回答 1

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如果你print(is_filled = (df.isnull() & df_filled.notnull()) | df.notnull())那么你会看到你有 和 的混合True体NaN。所以解决方案是将NaN值替换为False：

底部的代码片段：

df=df.drop('date',1)
is_filled = (df.isnull() & df_filled.notnull()) | df.notnull() 
is_filled = is_filled.fillna(False) # Fix here
df_filled[is_filled]=df_filled[is_filled].applymap(lambda x: '_2D' if pd.notnull(x)  else np.nan)
于 2018-03-08T23:50:24.277 回答