Python,pandas:如何将一个系列附加到数据帧

我有以下数据帧df1:

import pandas as pd
data = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy', 'Lisa', 'Molly', 'Lisa', 'Molly', 'Fred'], 
             'gender': ['m', 'f', 'f', 'm', 'f', 'f', 'f', 'f','f', 'm'], 
   }
df1 = pd.DataFrame(data, index = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10])

我想创建一个包含一些标准和一些自定义汇总统计信息df2的表.

df2 = df1.describe()
df2.rename(index={'top':'mode'},inplace=True)
df2.rename(index={'freq':'mode freq'},inplace=True)
df2

DF2:

                  gender    name
        count       10      10
        unique      2       7
        mode        f       Molly
        mode freq   7       3

我想为第二种模式向df2追加一行,为第二种模式的频率追加一行:

例:

                gender  name
    count       10      10
    unique      2       7
    mode        f       Molly
    mode freq   7       3
    2nd mode    m       Lisa
    2nd freq    3       2

我发现你可以得到第二种模式&这样做的频率:

my_series
for column in df1:
   my_series=df1[column].value_counts()[1:2]
   print(my_series)

但是如何将其附加到df2?

最佳答案 有柜台

from collections import Counter

def f(s):
    return pd.Series(Counter(s).most_common(2)[1], ['mode2', 'mode2 freq'])

df1.describe().rename(dict(top='mode1', freq='mode1 freq')).append(df1.apply(f))

             name gender
count          10     10
unique          7      2
mode1       Molly      f
mode1 freq      3      7
mode2        Lisa      m
mode2 freq      2      3

value_counts

没有Counter的同样的事情

def f(s):
    c = s.value_counts()
    return pd.Series([s.iat[1], s.index[1]], ['mode2', 'mode2 freq'])

df1.describe().rename(dict(top='mode1', freq='mode1 freq')).append(df1.apply(f))

Numpy位

def f(s):
    f, u = pd.factorize(s)
    c = np.bincount(f)
    i = np.argpartition(c, -2)[-2]
    return pd.Series([u[i], c[i]], ['mode2', 'mode2 freq'])

df1.describe().rename(dict(top='mode1', freq='mode1 freq')).append(df1.apply(f))
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