我有以下数据帧df1:
import pandas as pd data = {'name': ['Jason','Molly','Tina','Jake','Amy','Lisa','Fred'],'gender': ['m','f','m','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?
解决方法
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]],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]],freq='mode1 freq')).append(df1.apply(f))
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