Python如何实现批量重命名文件操作?

2026-05-21 16:521阅读0评论SEO资讯
  • 内容介绍
  • 文章标签
  • 相关推荐

本文共计288个文字,预计阅读时间需要2分钟。

Python如何实现批量重命名文件操作?

pythondef rename_values(data, new_values): Rename keys in a dictionary based on a mapping of old to new values.

Args: data (dict): The original dictionary with old values as keys. new_values (dict): A dictionary mapping old values to new keys.

Returns: dict: A new dictionary with keys renamed according to the new_values mapping. new_data={} for key, value in data.items(): new_key=new_values.get(value, key) new_data[new_key]=value return new_data


Python如何实现批量重命名文件操作?

python_rename

Replacing Values
# 替换值
# 利⽤fillna⽅法填充缺失数据可以看做值替换的⼀种特殊情况
data = pd.Series([1., -999., 2., -999., -1000., 3.])
data
0 1.0
1 -999.0
2 2.0
3 -999.0
4 -1000.0
5 3.0
dtype: float64
# 以利⽤replace来产⽣⼀个新的Series(除⾮传⼊inplace=True) 替换
data.replace(-999, np.nan)
0 1.0
1 NaN
2 2.0
3 NaN
4 -1000.0
5 3.0
dtype: float64
# 替换多个值
data.replace([-999, -1000], np.nan)
# 要让每个值有不同的替换值,可以传递⼀个替换列表:
data.replace([-999, -1000], [np.nan, 0])
# 传⼊的参数也可以是字典:
data.replace({-999: np.nan, -1000: 0})
0 1.0
1 NaN
2 2.0
3 NaN
4 0.0
5 3.0
dtype:


本文共计288个文字,预计阅读时间需要2分钟。

Python如何实现批量重命名文件操作?

pythondef rename_values(data, new_values): Rename keys in a dictionary based on a mapping of old to new values.

Args: data (dict): The original dictionary with old values as keys. new_values (dict): A dictionary mapping old values to new keys.

Returns: dict: A new dictionary with keys renamed according to the new_values mapping. new_data={} for key, value in data.items(): new_key=new_values.get(value, key) new_data[new_key]=value return new_data


Python如何实现批量重命名文件操作?

python_rename

Replacing Values
# 替换值
# 利⽤fillna⽅法填充缺失数据可以看做值替换的⼀种特殊情况
data = pd.Series([1., -999., 2., -999., -1000., 3.])
data
0 1.0
1 -999.0
2 2.0
3 -999.0
4 -1000.0
5 3.0
dtype: float64
# 以利⽤replace来产⽣⼀个新的Series(除⾮传⼊inplace=True) 替换
data.replace(-999, np.nan)
0 1.0
1 NaN
2 2.0
3 NaN
4 -1000.0
5 3.0
dtype: float64
# 替换多个值
data.replace([-999, -1000], np.nan)
# 要让每个值有不同的替换值,可以传递⼀个替换列表:
data.replace([-999, -1000], [np.nan, 0])
# 传⼊的参数也可以是字典:
data.replace({-999: np.nan, -1000: 0})
0 1.0
1 NaN
2 2.0
3 NaN
4 0.0
5 3.0
dtype: