程式碼:
a = 1
lsta = list(a)
print(lsta,type(lsta),len(lsta))
輸出:
Traceback (most recent call last):
File “C:\Python\Radar_20221005\untitled1.py”, line 3, in <module>
lsta = list(a)
TypeError: ‘int’ object is not iterable
int無法取list()
如果取array()呢?
程式碼:
import numpy as np
a = 1
arya = np.array(a)
print(arya, type(arya), len(arya))
輸出:
Traceback (most recent call last):
File “C:\Python\Radar_20221005\untitled1.py”, line 7, in <module>
print(arya,type(arya),len(arya))
TypeError: len() of unsized object
int可以取array(),
只是長度0 (不要誤會長度1)
所以取len()時錯誤
empty list: []長度也是0
去掉len()

3(1+2)的左右邊沒有[ ] 包覆
type為ndarray (0-dimensional)
用法同int
numpy官網:

2D array的運算:

推薦hahow線上學習python: https://igrape.net/30afN

![Python:如何將folder_path & file_name合併為file_path? fpath = os.path.join (folder , fname) #不需要[ ]包覆folder,fname; fpath1 = “\\”.join( [folder , fname] ) #需要[ ] 包覆folder,fname ; 反過來講,file_path如何拆分為folder_path & file_name? os.path.dirname() ; os.path.basename() ; file_name如何拆分為主檔名與副檔名os.path.splitext() #split(分裂) ext Python:如何將folder_path & file_name合併為file_path? fpath = os.path.join (folder , fname) #不需要[ ]包覆folder,fname; fpath1 = “\\”.join( [folder , fname] ) #需要[ ] 包覆folder,fname ; 反過來講,file_path如何拆分為folder_path & file_name? os.path.dirname() ; os.path.basename() ; file_name如何拆分為主檔名與副檔名os.path.splitext() #split(分裂) ext](https://i2.wp.com/savingking.com.tw/wp-content/uploads/2023/07/20230717184401_87.png?quality=90&zoom=2&ssl=1&resize=350%2C233)
![Python如何做excel的樞紐分析? DataFrame .pivot_table (values=None, index=None, columns=None, aggfunc=’mean’) ; df.groupby([‘A’, ‘B’, ‘C’], sort=False)[‘D’].sum().unstack(‘C’) Python如何做excel的樞紐分析? DataFrame .pivot_table (values=None, index=None, columns=None, aggfunc=’mean’) ; df.groupby([‘A’, ‘B’, ‘C’], sort=False)[‘D’].sum().unstack(‘C’)](https://i0.wp.com/savingking.com.tw/wp-content/uploads/2023/03/20230325141855_86.png?quality=90&zoom=2&ssl=1&resize=350%2C233)




![一文搞懂Python pandas.DataFrame去重:df.drop_duplicates() 與 df[~df.duplicated()] 的等價、差異與最佳實踐 一文搞懂Python pandas.DataFrame去重:df.drop_duplicates() 與 df[~df.duplicated()] 的等價、差異與最佳實踐](https://i1.wp.com/savingking.com.tw/wp-content/uploads/2025/08/20250808202701_0_66f9bc.png?quality=90&zoom=2&ssl=1&resize=350%2C233)


近期留言