嘗試使用函數來填充數據幀缺失值和應用（）

Question

我想基礎上，Counrty

 
def avgtemp(cols): 
    AverageTemperature = cols[0] 
    Country = cols[1] 

    if state.isnull(AverageTemperature): 

     if Country == "Brazil": 
      return 23.770601 

     elif Country == "Russia": 
      return 1.808555 

     elif Country == "United State": 
      return 10.701555 

     elif Country == "Canada": 
      return -1.321079 

     elif Country == "India": 
      return 22.534576 

     elif Country == "China": 
      return 11.206830 

     elif Country == "Australia": 
      return 17.664222 

     else: 
      return 8.9931 

    else: 
     return AverageTemperature 
state['AverageTemperature'] = state[['AverageTemperature','Country']].apply(avgtemp,axis=1) 

填寫使用不同的值數據集的缺失值，但我不斷收到此錯誤

 
--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
in() 
----> 1 state['AverageTemperature'] = state[['AverageTemperature','Country']].apply(avgtemp,axis=1) 

C:\Anaconda3\lib\site-packages\pandas\core\frame.py in apply(self, func, axis, broadcast, raw, reduce, args, **kwds) 
    4059      if reduce is None: 
    4060       reduce = True 
-> 4061      return self._apply_standard(f, axis, reduce=reduce) 
    4062    else: 
    4063     return self._apply_broadcast(f, axis) 

C:\Anaconda3\lib\site-packages\pandas\core\frame.py in _apply_standard(self, func, axis, ignore_failures, reduce) 
    4155    try: 
    4156     for i, v in enumerate(series_gen): 
-> 4157      results[i] = func(v) 
    4158      keys.append(v.name) 
    4159    except Exception as e: 

in avgtemp(cols) 
     3  Country = cols[1] 
     4 
----> 5  if state.isnull(AverageTemperature): 
     6 
     7   if Country == "Brazil": 

TypeError: ('isnull() takes 1 positional argument but 2 were given', 'occurred at index 0') 

Answer 1

您可以isnull找到loc價值觀和map取代：

state = pd.DataFrame({'Country':['Brazil','Russia','Slovakia','Russia'], 
        'AverageTemperature':[np.nan, np.nan, np.nan, 23]}) 
print (state) 
    AverageTemperature Country 
0     NaN Brazil 
1     NaN Russia 
2     NaN Slovakia 
3    23.0 Russia 

#add all values to dict 
d = {"Brazil":23.770601, "Russia":1.808555, ...} 

mask = state['AverageTemperature'].isnull() 
state.loc[mask, 'AverageTemperature'] = state.loc[mask, 'Country'].map(d) 
#all another NaNs replace by default value 
state['AverageTemperature'] = state['AverageTemperature'].fillna(8.9931) 
print (state) 
    AverageTemperature Country 
0   23.770601 Brazil 
1   1.808555 Russia 
2   8.993100 Slovakia 
3   23.000000 Russia