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))