如何使用Python熊猫将某些列扩展为行

例如

Animal  Food 
rabbit  grass 
rabbit  carrots 
rabbit  cabbage 
dog  carrots 
horse  grass 
horse  hay

我想是这样的：

Animal  Food1 Food2  Food3 
rabbit  grass carrots cabbage 
dog  carrots 
horse  grass hay

或者是这样的：

Animal  Grass  Carrots Cabbage  Hay 
rabbit  True  True  True  False 
dog   False  True  False  False 
horse  True  False  False  True

我试过透视表，融化和堆栈，但仍无法弄清楚如何做这个。任何帮助将不胜感激。谢谢！！

来源

2017-06-13 qhan

WEEE ...有很多方法。我爱熊猫！ –

选项1
groupby与size

df.groupby(['Animal', 'Food']).size().unstack(fill_value=0).astype(bool) 

Food cabbage carrots grass hay 
Animal         
dog  False  True False False 
horse  False False True True 
rabbit  True  True True False

s = df.groupby('Animal').Food.apply(list) 
pd.DataFrame(s.values.tolist(), s.index).add_prefix('Food').fillna('') 

      Food0 Food1 Food2 
Animal       
dog  carrots     
horse  grass  hay   
rabbit grass carrots cabbage

选项2
groupby与value_counts

df.groupby('Animal').Food.value_counts().unstack(fill_value=0).astype(bool) 

Food cabbage carrots grass hay 
Animal         
dog  False  True False False 
horse  False False True True 
rabbit  True  True True False

选项3
groupby和str.get_dummies

df.groupby('Animal').Food.apply('|'.join).str.get_dummies().astype(bool) 

     cabbage carrots grass hay 
Animal         
dog  False  True False False 
horse  False False True True 
rabbit  True  True True False

选择4
pandas.factorize与numpy.bincount

f1, u1 = pd.factorize(df.Animal.values) 
f2, u2 = pd.factorize(df.Food.values) 

n = u1.size 
m = u2.size 

b = np.bincount(f1 * m + f2, minlength=n * m).reshape(n, m) 

pd.DataFrame(b.astype(bool), u1, u2) 

     grass carrots cabbage hay 
rabbit True  True  True False 
dog  False  True False False 
horse True False False True

选项5
很烦......所以有更多

f, u = pd.factorize(df.Animal.values) 
n = u.size 

a = [[] for _ in range(n)] 
[a[i].append(food) for i, food in zip(f, df.Food)]; 
pd.DataFrame(a, u).rename(columns=lambda x: x+1).add_prefix('Food').fillna('') 

      Food1 Food2 Food3 
rabbit grass carrots cabbage 
dog  carrots     
horse  grass  hay

来源

2017-06-13 18:36:47 piRSquared

想出您可以使用：

df = pd.pivot(index=df['Animal'], 
       columns=df.groupby('Animal').cumcount().add(1).astype(str), 
       values=df['Food']) 
     .add_prefix('Food').fillna('') 
print (df) 
      Food1 Food2 Food3 
Animal       
dog  carrots     
horse  grass  hay   
rabbit grass carrots cabbage

或者：

df = pd.crosstab(df['Animal'], df['Food']).astype(bool) 
print (df) 
Food cabbage carrots grass hay 
Animal         
dog  False  True False False 
horse  False False True True 
rabbit  True  True True False

来源

2017-06-13 18:36:54 jezrael

您可以使用交叉

pd.crosstab(df.Animal, df.Food).astype(bool) 


Food cabbage carrots grass hay 
Animal    
dog  False True False False 
horse False False True True 
rabbit True True True False

来源

2017-06-13 18:39:37 Vaishali

df_out = df.set_index(['Animal','Food']).assign(Value=True).unstack().fillna(False) 
df_out.columns = df_out.columns.droplevel()

输出：

Food cabbage carrots grass hay 
Animal         
dog  False  True False False 
horse  False False True True 
rabbit  True  True True False

来源

2017-06-13 18:41:43

如何使用Python熊猫将某些列扩展为行

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