Python 如何使用pandas取消数据帧透视

Python 如何使用pandas取消数据帧透视,python,pandas,dataframe,melt,Python,Pandas,Dataframe,Melt,例如,我有这样一个数据帧 df = {'name':['Jennifer','Vivian','Trisha'], 'married':[1,1,0], 'Mon': [0, 0,1], 'Tu':[1,0,0], 'Wed':[0,1,0]} 如何将虚拟变量融为一列,如下所示: 我尝试使用pd.melt(),但它只是将几列堆叠成一列,并更改列的长度。有人能帮我吗?提前谢谢你 这是一种方法 res = pd.melt(df, id_vars=['ma

例如,我有这样一个数据帧

df = {'name':['Jennifer','Vivian','Trisha'],
     'married':[1,1,0],
     'Mon': [0, 0,1],
     'Tu':[1,0,0],
     'Wed':[0,1,0]}

如何将虚拟变量融为一列,如下所示:

我尝试使用pd.melt(),但它只是将几列堆叠成一列,并更改列的长度。有人能帮我吗?提前谢谢你

这是一种方法

res = pd.melt(df, id_vars=['married', 'name'], value_vars=['Mon', 'Tu', 'Wed'],
              var_name='Workday')

res = res[res['value'] == 1].reset_index(drop=True)

d = {0: 'single', 1: 'married'}
res['married'] = res['married'].map(d)

print(res)

#    married      name Workday  value
# 0   single    Trisha     Mon      1
# 1  married  Jennifer      Tu      1
# 2  married    Vivian     Wed      1
这应该起作用:

df.replace({'married':{1:'Married', 0: 'Single'}}). \
   melt(id_vars=['married', 'name'], var_name='Workday'). \
   query('value == 1'). \
   drop('value', axis=1)

#    married      name Workday
# 2   Single    Trisha     Mon
# 3  Married  Jennifer      Tu
# 7  Married    Vivian     Wed