你问的是所有条件都为真的条件，所以框架的len就是答案，除非我误解了你的问题

In [17]: df = DataFrame(randn(20,4),columns=list('ABCD'))

In [18]: df[(df['A']>0) & (df['B']>0) & (df['C']>0)]
Out[18]: 
           A         B         C         D
12  0.491683  0.137766  0.859753 -1.041487
13  0.376200  0.575667  1.534179  1.247358
14  0.428739  1.539973  1.057848 -1.254489

In [19]: df[(df['A']>0) & (df['B']>0) & (df['C']>0)].count()
Out[19]: 
A    3
B    3
C    3
D    3
dtype: int64

In [20]: len(df[(df['A']>0) & (df['B']>0) & (df['C']>0)])
Out[20]: 3

字符串

在Pandas中，我喜欢使用shape属性来获取行数。

df[df.A > 0].shape[0]

字符串
根据需要，给出符合条件A > 0的行数。

为了提高性能，不应该使用 predicate 来计算DataFrame。最好直接使用sum(predecate)，如下所示：

In [1]: import pandas as pd
        import numpy as np
        df = pd.DataFrame(np.random.randn(20,4),columns=list('ABCD'))
 

In [2]: df.head()
Out[2]:
          A         B         C         D
0 -2.019868  1.227246 -0.489257  0.149053
1  0.223285 -0.087784 -0.053048 -0.108584
2 -0.140556 -0.299735 -1.765956  0.517803
3 -0.589489  0.400487  0.107856  0.194890
4  1.309088 -0.596996 -0.623519  0.020400

In [3]: %time sum((df['A']>0) & (df['B']>0))
CPU times: user 1.11 ms, sys: 53 µs, total: 1.16 ms
Wall time: 1.12 ms
Out[3]: 4

In [4]: %time len(df[(df['A']>0) & (df['B']>0)])
CPU times: user 1.38 ms, sys: 78 µs, total: 1.46 ms
Wall time: 1.42 ms
Out[4]: 4

字符串
请记住，这种技术只适用于计算符合 predicate 的行数。

你可以使用query方法来获取结果的shape。例如：

A  B  C
0  1  1  x
1  2  2  y
2  3  3  z

df.query("A == 2 & B > 1 & C != 'z'").shape[0]

字符串
输出量：

import pandas as pd
data = {'title': ['Manager', 'Technical Analyst', 'Software Engineer', 'Sales Manager'], 'Description': [
'''a man or woman who controls an organization or part of an organization,a person who looks after the business affairs of a singer, actor, etc''',
'''Technical analysts, also known as chartists or technicians, employ technical analysis in their trading and research. Technical analysis looks for price patterns and trends based on historical performance to identify signals based on market sentiment and psychology.''',
'''A software engineer is a person who applies the principles of software engineering to design, develop, maintain, test, and evaluate computer software. The term programmer is sometimes used as a synonym, but may also lack connotations of engineering education or skills.''',
'''A sales manager is someone who leads and supervises sales agents and runs the day-to-day sales operations of a business. They oversee the sales strategy, set sales goals, and track sales performance'''
]}
df = pd.DataFrame(data)
data2 = {'title': ['Manager', 'Technical Analyst', 'Software Engineer', 'Sales Manager'], 'Keywords': [
['organization','business','people','arrange']
,['technicians','analysis','research','business']
,['engineering', 'design', 'develop', 'maintain']
,['supervises', 'agents','business','performance','target']
]}
df2 = pd.DataFrame(data2)
print(df2)
df2=df2.explode('Keywords')

print(df2)
print("checking df3")
df3=df.merge(df2,how='left',on='title')
print(df3)
df3['match'] = df3.apply(lambda x: x.Keywords in x.Description, axis=1)
print(df3)
df4=df3.loc[df3['match']==True].groupby(['Description']).count()
print(df4)

字符串