小编Ney*_*res的帖子

在numpy.sum()有参数调用keepdims.它有什么作用？

正如您在文档中看到的那样:http: //docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html

numpy.sum(a, axis=None, dtype=None, out=None, keepdims=False)[source]
Sum of array elements over a given axis.

Parameters: 
...
keepdims : bool, optional
    If this is set to True, the axes which are reduced are left in the result as
    dimensions with size one. With this option, the result will broadcast
    correctly against the input array.
...

嘿，我正在创建一个 jupyter 笔记本，想要安装：

https://github.com/voice32/stock_market_indicators/blob/master/indicators.py 这是一个Python程序

不知道如何直接执行此操作，以便任何下载笔记本的人都可以点击“全部运行”，然后查看结果

选项 1）执行类似的操作： from https://github.com/voice32/stock_market_indicators/blob/master/indicators.py import Indicators.py

当然这是行不通的

给定

patient_id  test_result has_cancer
0   79452   Negative    False
1   81667   Positive    True
2   76297   Negative    False
3   36593   Negative    False
4   53717   Negative    False
5   67134   Negative    False
6   40436   Negative    False

如何在python中的列中计算False或True？

我一直在尝试：

# number of patients with cancer

number_of_patients_with_cancer= (df["has_cancer"]==True).count()
print(number_of_patients_with_cancer)