df['人员类型'].value_counts()

df['人员类型'].value_counts() is a method used to count the number of occurrences of each unique value in the '人员类型' column of a pandas DataFrame df, and return the result as a new DataFrame with the count of each value sorted in descending order.
For example, if the '人员类型' column contains the following values: '员工', '经理', '实习生', '员工', '实习生', '员工', '经理', '实习生', '实习生', '员工', the output of df['人员类型'].value_counts() would be:
实习生 4
员工 4
经理 2

This means that '实习生' and '员工' both occurred 4 times, and '经理' occurred 2 times in the '人员类型' column of the DataFrame.

相关问题

df.value_counts()

As an AI language model, I don't have access to any specific dataframe to execute code. However, in general, df.value_counts() is a method used in pandas library of Python to count the number of occurrences of each unique value in a series or dataframe column. It returns a new series with counts of unique values in descending order.

df.LoyaltyIsAutoLost.value_counts()

这行代码计算了数据集df中LoyaltyIsAutoLost列中每个取值的数量，返回一个Series对象。其中，Series对象的索引是LoyaltyIsAutoLost列中的取值，值是每个取值在数据集中出现的次数。通过调用value_counts函数，可以了解数据集中各个取值的分布情况。
例如，如果LoyaltyIsAutoLost列中有两个取值0和1，那么这行代码的输出结果将会是一个长度为2的Series对象，其中包含了0和1两个索引，以及它们在数据集中出现的次数。这个结果可以帮助我们了解数据集中目标变量的分布情况，从而为后续的建模和评估工作提供参考。