Python3，与pandas.dataframe，如何通过一些规则选择某些数据来显示

Question

我有一个pandas.dataframe，我想通过一些规则选择某些数据。

下面的代码生成数据帧

import datetime 
import pandas as pd 
import numpy as np 

today = datetime.date.today() 
dates = list() 
for k in range(10): 
    a_day = today - datetime.timedelta(days=k) 
    dates.append(np.datetime64(a_day)) 

np.random.seed(5) 
df = pd.DataFrame(np.random.randint(100, size=(10, 3)), 
        columns=('other1', 'actual', 'other2'), 
        index=['{}'.format(i) for i in range(10)]) 

df.insert(0, 'dates', dates) 
df['err_m'] = np.random.rand(10, 1)*0.1 
df['std'] = np.random.rand(10, 1)*0.05 
df['gain'] = np.random.rand(10, 1) 

现在，我想通过以下规则进行选择：

1. compute the sum of 'err_m' and 'std', then sort the df so that the sum is descending 
2. from the result of step 1, select the part where 'actual' is > 50  

感谢

Answer 1

1. 创建一个新的列，然后排序这一个：

   df['errsum'] = df['err_m'] + df['std'] 
   # Return a sorted dataframe 
   df_sorted = df.sort('errsum', ascending = False) 
   

2. 选择要

   # Create an array with True where the condition is met 
   selector = df_sorted['errsum'] > 50 
   # Return a view of sorted_dataframe with only the lines you want 
   df_sorted[selector]