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@ryo_naka

DataFrameにてMeanを使う

値を含むDataFrameにてMeanを使うと平均値のDataFrameが取得できる。
その際に対象項目にNULLが含まれている場合にどうなるかを確認する。

※今回の希望としてはNULLの分は除いて平均をとってほしい。。


import pandas as pd

df_ExistNone = pd.DataFrame({'a': [1, 2, 1,None, 3],
                   'b': [0.4, 1.1,None, 0.1, 0.8],
                   'c': ['X', 'Y',None, 'X', 'Z'],
                   'd': ['3',None, '5', '2', '1'],
                   'e': [True,None, True, False, True]})

df = pd.DataFrame({'a': [1, 2, 1, 3],
                   'b': [0.4, 1.1, 0.1, 0.8],
                   'c': ['X', 'Y', 'X', 'Z'],
                   'd': ['3', '5', '2', '1'],
                   'e': [True, True, False, True]})

df_0 = pd.DataFrame({'a': [1, 2, 1,0, 3],
                   'b': [0.4, 1.1,0, 0.1, 0.8],
                   'c': ['X', 'Y',None, 'X', 'Z'],
                   'd': ['3','0', '5', '2', '1'],
                   'e': [True,None, True, False, True]})

print(df)
print(df_ExistNone)
print(df_0)

print("-------------------")

print(df.mean())
print(df_ExistNone.mean())
print(df_0.mean())

結果

   a    b  c  d      e
0  1  0.4  X  3   True
1  2  1.1  Y  5   True
2  1  0.1  X  2  False
3  3  0.8  Z  1   True
     a    b     c     d      e
0  1.0  0.4     X     3   True
1  2.0  1.1     Y  None   None
2  1.0  NaN  None     5   True
3  NaN  0.1     X     2  False
4  3.0  0.8     Z     1   True
   a    b     c  d      e
0  1  0.4     X  3   True
1  2  1.1     Y  0   None
2  1  0.0  None  5   True
3  0  0.1     X  2  False
4  3  0.8     Z  1   True

-------------------
a      1.75
b      0.60
d    880.25
e      0.75
dtype: float64
a    1.75
b    0.60
e    0.75
dtype: float64
a       1.40
b       0.48
d    6104.20
e       0.75
dtype: float64

Noneの項目については、計算から除外されていることがわかる

Noneを含みたい場合は
skipna = False/True

print(df_ExistNone.mean(skipna = True))
print(df_ExistNone.mean(skipna = False))
a    1.75
b    0.60
e    0.75
dtype: float64
a   NaN
b   NaN
dtype: float64
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Help us understand the problem. What are the problem?