Question

df = pd.DataFrame({'From_To': ['LoNDon_paris', 'MAdrid_miLAN', 'londON_StockhOlm','Budapest_PaRis', 'Brussels_londOn'],
'FlightNumber': [10045, np.nan, 10065, np.nan, 10085],
'RecentDelays':  [[23, 47], [], [24, 43, 87], [13], [67, 32]], 
'Airline': ['KLM(!)', '<Air France> (12)', '(British Airways. )', '12. Air France', '"Swiss Air"']})

df

               Airline  FlightNumber           From_To  RecentDelays
0               KLM(!)       10045.0      LoNDon_paris      [23, 47]
1    <Air France> (12)           NaN      MAdrid_miLAN            []
2  (British Airways. )       10065.0  londON_StockhOlm  [24, 43, 87]
3       12. Air France           NaN    Budapest_PaRis          [13]
4          "Swiss Air"       10085.0   Brussels_londOn      [67, 32]

缺少FlightNumber列中的某些值。这些数字意味着每行增加10，因此需要设置10055和10075。填写这些缺失的数字，并使列成为整数列（而不是浮点列）。

Answer 1

似乎是pd.Series.interpolate的一个很好的用例：

df['FlightNumber'] = df['FlightNumber'].interpolate().astype(int)
df

               Airline  FlightNumber           From_To  RecentDelays
0               KLM(!)         10045      LoNDon_paris      [23, 47]
1    <Air France> (12)         10055      MAdrid_miLAN            []
2  (British Airways. )         10065  londON_StockhOlm  [24, 43, 87]
3       12. Air France         10075    Budapest_PaRis          [13]
4          "Swiss Air"         10085   Brussels_londOn      [67, 32]

默认方法是'linear'，只要FlightNumber线性增加，就是这里所需要的。

Answer 2

希望这行得通。

for i in range(1, df['FlightNumber'].count() + 1):
      if pd.isnull(df.loc[i,'FlightNumber']):
          df.loc[i, 'FlightNumber'] = df.loc[i-1, 'FlightNumber'] + 10

Answer 3

尝试以下代码：-

df['FlightNumber'] = df['FlightNumber'].interpolate().astype(int)

数据缺失填充NAN加10

3 个答案: