pandas 笔记：to_numeric

1 函数介绍

它用于将参数转换为数值类型

这个函数尤其适用于在数据清洗过程中，将数据集中的字符串或其他类型的列转换为数值型数据。

pandas.to_numeric(
    arg, 
    errors='raise', 
    downcast=None, 
    dtype_backend=_NoDefault.no_default)

2 参数说明

3 举例说明

3.1 downcast

import pandas as pd
s = pd.Series(['1.0', '2', -3])
pd.to_numeric(s)
'''
0    1.0
1    2.0
2   -3.0
dtype: float64
'''

pd.to_numeric(s, downcast='integer')
'''
0    1
1    2
2   -3
dtype: int8
'''

3.2 errors

s = pd.Series(['apple', '1.0', '2', -3])
pd.to_numeric(s, errors='ignore')
'''
0    apple
1      1.0
2        2
3       -3
dtype: object
'''

pd.to_numeric(s, errors='coerce')
'''
0    NaN
1    1.0
2    2.0
3   -3.0
dtype: float64
'''

pd.to_numeric(s, errors='raise')
'''
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
File D:\conda\lib\site-packages\pandas\_libs\lib.pyx:2369, in pandas._libs.lib.maybe_convert_numeric()

ValueError: Unable to parse string "apple"

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
Cell In[40], line 1
----> 1 pd.to_numeric(s, errors='raise')

File D:\conda\lib\site-packages\pandas\core\tools\numeric.py:185, in to_numeric(arg, errors, downcast)
    183 coerce_numeric = errors not in ("ignore", "raise")
    184 try:
--> 185     values, _ = lib.maybe_convert_numeric(
    186         values, set(), coerce_numeric=coerce_numeric
    187     )
    188 except (ValueError, TypeError):
    189     if errors == "raise":

File D:\conda\lib\site-packages\pandas\_libs\lib.pyx:2411, in pandas._libs.lib.maybe_convert_numeric()

ValueError: Unable to parse string "apple" at position 0
'''