The following syntax shows to apply a function to multiple columns of DataFrame:df[['column1','column1']].apply(anyFun); Where, column1 and column2 are the column names on which we have to apply the function, and "function" has some operations that will be performed on the columns....
(self, key, value) 1284 ) 1285 1286 check_dict_or_set_indexers(key) 1287 key = com.apply_if_callable(key, self) -> 1288 cacher_needs_updating = self._check_is_chained_assignment_possible() 1289 1290 if key is Ellipsis: 1291 key = slice(None) ~/work/pandas/pandas/pandas/core/seri...
Pandas: Create two new columns in a DataFrame with values calculated from a pre-existing column Pandas crosstab() function with example How to sum values in a column that matches a given condition using Pandas? How to use melt function in pandas?
We can create a Pandas pivot table with multiple columns and return reshaped DataFrame. By manipulating given index or column values we can reshape the data based on column values. Use thepandas.pivot_tableto create a spreadsheet-stylepivot table in pandas DataFrame. This function does not suppo...
In Pandas, the apply() function can indeed be used to return multiple columns by returning a pandas Series or DataFrame from the applied function. In this article, I will explain how to return multiple columns from the pandas apply() function. Advertisements Key Points – apply() allows for...
df['修改的列'] = df['条件列'].apply(调用函数名) import pandas as pd def test(): # 读取Excel文件 df = pd.read_excel('测试数据.xlsx') def modify_value(x): if x < 5: return '是' elif x < 10: return '否' else: return 'x' # 插入列 for col_num in range(4, 9): df....
df.columns() # 查看字段()名称 df.describe() # 查看汇总统计 s.value_counts() # 统计某个值出现次数 df.apply(pd.Series.value_counts) # 查看DataFrame对象中每列的唯值和计数 df.isnull().any() # 查看是否有缺失值 df[df[column_name].duplicated()] # 查看column_name字段数据重复的数据信息 ...
date_range('20140721',periods=3)],names=['symbol','date']),columns=['value'])In[5]:df ...
How do I select multiple rows and columns from a pandas DataFrame? When should I use the "inplace" parameter in pandas? How do I make my pandas DataFrame smaller and faster? How do I use pandas with scikit-learn to create Kaggle submissions? More of your pandas questions answered! How ...
columns=['numbers', 'colors']) df['colName'] = 'colors' from pathos.multiprocessing import Pool tic = time.perf_counter() result = Pool(8).imap(enrich_row, df.iterrows(), chunksize=1) df = pd.DataFrame(result) toc = time.perf_counter() ...