Clean crisp code is your friend in these moments. The same goes for your data type: you will likely want to rename columns in your data frame to make it easier to understand and maintain each query and parameter over time, so that the field names in your dataframe can be understood and ...
Python - 重命名Pandas DataFrame的列 要重新命名DataFrame的列,请使用 rename() 方法。将要重命名的列名设置到rename()方法的“columns”参数中。例如,将“ Car ”列更改为“ Car Name ” - dataFrame.rename(columns={'Car': 'Car Name'}, inplace=False) 首先,读
new_df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'}, inplace=True) # inplace = True 目的是修改原有Dataframe,不生成新的 DataFrame 参考http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.rename.html # rename 可以修改 Series 的index值 >>> ...
Renaming and Combining 重命名、合并 7.1 Renaming 重命名把名字改成我们喜欢的,更合适的,rename(),可以把索引名、列名更改 wine_rev.rename(columns 51620 【译】Python中的数据清洗 |Pythonic Data Cleaning With NumPy and Pandas(三) Pandas(一) 【译】Python中的数据清洗 |Pythonic Data Cleaning With NumPy...
pythonpandasreplacedataframerename 答案 使用df.rename()函数并引用要重命名的列。并非所有列都必须重命名: df = df.rename(columns={'oldName1': 'newName1', 'oldName2': 'newName2'}) # Or rename the existing DataFrame (rather than creating a copy) df.rename(columns={'oldName1': 'newName1...
The resulting DataFrame will have all the valid business days as the index and columns for the market opening datetime (market_open) and closing datetime (market_close). All time zones are set to UTC. To convert to the local exchange time use pandas tz_convert and the self.tz to get ...