Python 从 2 列中随机 Select

发布于04月13日

如何从两列中随机 Select ？

谢谢

import pandas as pd
import numpy as np
import random
df = pd.read_csv('test.csv')
df.drop(['q','w'],inplace=True, axis=1)
n = 0
z = n+10
df=df.iloc[n:z]

g = df['a']
j = df['b']
#p = g+j

for i in range(5):
    cards_1 = np.random.choice(g, 4)
    print(cards_1)
print("\n")    
for ii in range(5):
    cards_2 = np.random.choice(j, 4)
    print(cards_2, sep = "\n")

推荐答案

Side Note:np.random.choice如果没有参数replace = FALSE，则可能会多次拾取一张卡，因为在提取对象后，该对象不会从 Select 池中移除.

考虑这个解决方案:


import pandas as pd
import numpy as np


# Dont worry about this. this is only to get some sample data
df = pd.DataFrame(np.transpose(np.array(
    [[7,8,9,10, "j", "q", "k", "a"],
     [7,8,9,10, "j", "q", "k", "a"],
     [7,8,9,10, "j", "q", "k", "a"]])),
                   columns=['a', 'b', 'c'])
                   
                   
# end of data
                   
# Choose two column names without replacement (dont pick same column twice or more)
random_colnames = np.random.choice(df.columns,2, replace = False)
# Custom colnames could be
#custom_colnames = ['a', 'b']


#drawn_cards = []

for col in random_colnames:
    # pick elements from column with replacement
    # and extend them to the list of already drawn cards
    for _ in range(5):
        # add replace = False if you do not want the same cardd picked more than once
        draw = np.random.choice(df[col],4)
        #drawn_cards.extend(draw) 
        print(draw)
    

# Print for showcase purpose
# print(drawn_cards)