在数据框（df）中添加一个新列，用于存储每个人的（总存在）/（总存在数+总数不存在）的值

Question

它是python Pandas数据框，命名为df。如何为其添加新列，为每个indivodual存储total present/(total present + total absent)

Answer 1

考虑数据框df

df = pd.DataFrame(
    np.random.choice([None, 'Absent', 'Present'], (10, 10))
)

您可以将pd.value_counts与normalize=True

一起使用

df.join(df.apply(pd.value_counts, 1, normalize=True).Present)

Answer 2

虚拟数据帧，为简单起见，我创建了a,b,c,d作为列名

import pandas as pd
df = pd.DataFrame({'a': ['jon','sam','dean','bob'],
               'b': ['present','present','absent','present'],
               'c':['absent','present','present','absent'],
               'd':['absent','absent','present','present']})

df['b1'] = df['b'].map({'present': 1, 'absent': 0})
df['c1'] = df['c'].map({'present': 1, 'absent': 0})
df['d1'] = df['d'].map({'present': 1, 'absent': 0})

df['sum_1'] = (df[['b1','c1','d1']] == 1).sum(axis=1)
df['sum_0'] = (df[['b1','c1','d1']] == 0).sum(axis=1)

df['present'] =((df['sum_1']* 1.0)/(df['sum_1']+df['sum_0']))

df[['a','b','c','d','present']]

或者你可以简单地使用@piRSquared建议的解决方案。

import pandas as pd
df = pd.DataFrame({'a': ['jon','sam','dean','bob'],
           'b': ['present','present','absent','present'],
           'c':['absent','present','present','absent'],
           'd':['absent','absent','present','present']})
df.assign(present=df.stack().map(dict(present=1, absent=0)).unstack().mean(1))