# Create a groupby object: by_sex_class
by_sex_class = titanic.groupby(["sex","pclass"]).count()
# Write a function that imputes median
def impute_median(series):
return series.fillna(series.median())
# Impute age and assign to titanic['age']
titanic.age = by_sex_class["age"].transform(impute_median)
# Print the output of titanic.tail(10)
print(titanic.tail(10))我不清楚我们如何分配列,“年龄”从修改(分组) df,by_sex_class,原始(未分组) df,泰坦尼克。
作业不会乱七八糟吗?
谢谢你的解释。
发布于 2018-11-01 01:29:41
我建议你用这个
df['age'].fillna(df.groupby(["sex","pclass"])['age'].transform('median'),inplace=True)https://stackoverflow.com/questions/53093828
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