cumprod 源码
时间: 2023-12-03 09:06:39 浏览: 28
对于cumprod函数的源码,根据引用中提到的发现,cumproduct函数和cumprod函数是一致的。因此,我们可以通过查看cumproduct函数的源码来了解cumprod函数的实现。遗憾的是,没有提供具体的源码信息。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *2* *3* [【numpy】np.cumprod的使用](https://blog.csdn.net/mimiduck/article/details/122772920)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 100%"]
[ .reference_list ]
相关问题
matlab cumprod
cumprod函数是Matlab中的一个函数,用于计算矩阵或向量中元素的累积乘积。cumprod函数的结果包含每一步计算的结果,而不仅仅是最终乘积的结果。
在使用cumprod函数时,可以指定参数dim来指定计算的方向。如果dim=1,那么函数会在列方向上计算累积乘积;如果dim=2,那么函数会在行方向上计算累积乘积。
通过cumprod函数,我们可以得到矩阵或向量中每个元素的累积乘积的结果,并进一步分析数据的变化趋势。
pandas cumprod
pandas.cumprod() is a function in the pandas library that returns the cumulative product of the elements in a pandas Series or DataFrame. It computes the product of all the elements from the beginning of the Series or DataFrame up to the current position.
Syntax:
```
DataFrame.cumprod(axis=None, skipna=True, *args, **kwargs)
```
Parameters:
- axis: 0 or 'index' for rows and 1 or 'columns' for columns. By default, it is None and applies cumprod() on the entire DataFrame.
- skipna: If True, it skips NaN values while performing the cumprod() operation, otherwise, it returns NaN.
Returns:
- A new pandas Series or DataFrame with the cumulative product of the elements.
Example:
```
import pandas as pd
df = pd.DataFrame({'A': [1, 2, 3, 4]})
print(df.cumprod())
```
Output:
```
A
0 1
1 2
2 6
3 24
```
相关推荐
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)