如何根据熊猫数据框中的多列获取百分比数?
我在数据框中有20列。 我列出其中4这里作为例子:如何根据熊猫数据框中的多列获取百分比数?
is_guarantee:0或1
hotel_star:0,1,2,3,4,5
ORDER_STATUS:40,60,80
旅程(标签): 0,1,2
is_guarantee hotel_star order_status journey 0 0 5 60 0
1 1 5 60 0
2 1 5 60 0
3 0 5 60 1
4 0 4 40 0
5 0 4 40 1
6 0 4 40 1
7 0 3 60 0
8 0 2 60 0
9 1 5 60 0
10 0 2 60 0
11 0 2 60 0
Click to View Image
但该系统需要输入发生矩阵像以下格式函数:
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身体能帮助吗?
df1 = pd.DataFrame(index=range(0,20)) df1['is_guarantee'] = np.random.choice([0,1], df1.shape[0])
df1['hotel_star'] = np.random.choice([0,1,2,3,4,5], df1.shape[0])
df1['order_status'] = np.random.choice([40,60,80], df1.shape[0])
df1['journey '] = np.random.choice([0,1,2], df1.shape[0])
回答:
我想你需要:
- 重塑通过
melt
和groupby
与size
得到计数,通过unstack
- 重塑然后划分和每行和参加
MultiIndex
到index
:
df = (df.melt('journey') .astype(str)
.groupby(['variable', 'journey','value'])
.size()
.unstack(1, fill_value=0))
df = (df.div(df.sum(1), axis=0)
.mul(100)
.add_prefix('journey_')
.set_index(df.index.map(' = '.join))
.rename_axis(None, 1))
print (df)
journey_0 journey_1
hotel_star = 2 100.000000 0.000000
hotel_star = 3 100.000000 0.000000
hotel_star = 4 33.333333 66.666667
hotel_star = 5 80.000000 20.000000
is_guarantee = 0 66.666667 33.333333
is_guarantee = 1 100.000000 0.000000
order_status = 40 33.333333 66.666667
order_status = 60 88.888889 11.111111
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