DataFrame.rename_axis(mapper[, axis, copy]) #Alter index and / or columns using input function or functions. DataFrame.reset_index([level, drop, …]) #For DataFrame with multi-level index, return new DataFrame with labeling information in the columns under the index names, defaulting to ‘l...
Help on function describe in module pandas.core.generic: describe(self: 'FrameOrSeries', percentiles=None, include=None, exclude=None, datetime_is_numeric=False) -> 'FrameOrSeries' Generate descriptive statistics. Descriptive statistics include those that summarize the central tendency, dispersion and...
DataFrame.rename_axis(mapper[, axis, copy, …])Alter index and / or columns using input function or functions. DataFrame.reset_index([level, drop, …])For DataFrame with multi-level index, return new DataFrame with labeling information in the columns under the index names, defaulting to ‘le...
values.DataFrame.head : Return the first `n` rows without re-ordering.Notes---This function cannot be used with all column types. For example, whenspecifying columns with `object` or `category`dtypes, ``TypeError`` israised.Examples--->>> df = pd.DataFrame({'population': [59000000, 6500...
df['OptimizedResult'] = df['Value'].apply(optimized_function) 在实际应用中,需要根据具体情况综合运用这些技巧来最大程度地优化 DataFrame 的性能。通过不断的实践和调整,我们能够使数据处理过程更加高效,为我们的数据分析和应用提供有力支持。 总之,优化 DataFrame 的性能是一个综合性的任务,需要我们从多个方面...
Combine two DataFrame objects and default to non-null values in frame calling the method. 函数应用&分组&窗口 方法 描述 DataFrame.apply(func[, axis, broadcast, …]) 应用函数 DataFrame.applymap(func) Apply a function to a DataFrame that is intended to operate elementwise, i.e. ...
df['new_col']=df['old_col'].apply(my_function) 但需要注意的是,在处理大数据集时,apply函数可能会耗费较长时间。此时可以考虑使用向量化操作或并行计算来提高效率。 后来【瑜亮老师】也补充了一个回答,如下图所示: 三、总结 大家好,我是皮皮。这篇文章主要盘点了一个Python基础的问题,文中针对该问题,给...
importpandasaspdimportnumpyasnppath='E:/Python/'df=pd.read_csv('filename.csv')# 去读csv文件df=pd.read_stata('filename.dta')# 读取stata数据#df=pd.read_csv(f, header=None, sep=',', names=['var1', 'var2', 'var3','var4', 'var5',]) #指定特定列名和分隔符df.head() ...
retained.Thedefaultbehaviour(None) dependsonthereturnvalueof the applied function: list-like results will be returnedasa Series of those. Howeverifthe apply function returns a Series these are expanded to columns. .. versionadded:: 0.23.0
for index, row in df.iterrows(): print(row) for row in df.itertuples(): print(row) ``` 使用apply()方法可以对dataframe的每一行或每一列进行自定义函数的操作,如下所示: ``` def my_function(row): return row['column1'] + row['column2'] df['new_column'] = df.apply(my_function,...