如何在Pandas的数据框子集中获得最大值?

时间:2014-03-15 12:35:03

标签: python indexing pandas subset

如何在Pandas的数据框子集中获得最大值?

例如,当我做

之类的事情时
statedata[statedata['state.region'] == 'Northeast'].ix[statedata['Murder'].idxmax()]

我得到一个KeyError,表明idxmax正在返回全局最大值Alabama的密钥,而不是查询子集中的最大值(当然缺少该密钥)。

有没有办法在熊猫上简明扼要地做到这一点?


作为参考,此处使用的数据来自R,使用

data(state)
statedata = cbind(data.frame(state.x77), state.abb, state.area, state.center, state.division, state.name, state.region)

然后从R导出并由Pandas导入。

1 个答案:

答案 0 :(得分:3)

您可以使用df.loc选择子数据框:

import pandas as pd
import pandas.rpy.common as com
import rpy2.robjects as ro

r = ro.r
statedata = r('''cbind(data.frame(state.x77), state.abb, state.area, state.center,
                 state.division, state.name, state.region)''')
df = com.convert_robj(statedata)
df.columns = df.columns.to_series().str.replace('state.', '')
subdf = df.loc[df['region']=='Northeast', 'Murder']
print(subdf)
# Connecticut       3.1
# Maine             2.7
# Massachusetts     3.3
# New Hampshire     3.3
# New Jersey        5.2
# New York         10.9
# Pennsylvania      6.1
# Rhode Island      2.4
# Vermont           5.5
# Name: Murder, dtype: float64
print(subdf.idxmax())

打印

New York

选择每个地区谋杀率最高的州(as of 1976):

In [24]: df.groupby('region')['Murder'].idxmax()
Out[24]: 
region
North Central    Michigan
Northeast        New York
South             Alabama
West               Nevada
Name: Murder, dtype: object