df_test = pd.concat([df_test, pd.DataFrame(columns=['size_kb', 'size_mb', 'size_gb'])]) %timeit result = df_test.apply(sizes_pass_series_return_series, axis=1) print('\nPandafied (pass series, return tuple, new
Pandas | Applying a function to Multiple columns: In this tutorial, we will learn how can we apply a function to multiple columns in a DataFrame with the help of example?ByPranit SharmaLast updated : April 19, 2023 How to Apply a Function to Multiple Columns of DataFrame?
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
#apply()函数使用案例# # 导入 numpy 库 import numpy as np # 导入 pandas 库 import pandas as pd # 定义 DataFrame # 数据为 3 行 4 列 s_data = pd.DataFrame([[5.1,3.5,1.4,0.2], [6.1,3.7,4.1,1.5], [5.8,2.7,5.1,1.9]], columns=['feature_one','feature_two','feature_three','fea...
(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/...
to_numeric(df['年龄'], errors='coerce') # 去除没用的列-照片列 df = df.drop(columns='照片') # 将排名变化列中的特殊值替换为 0 df['排名变化'] = df['排名变化'].replace('New', '0') # 将财富值变化列中的特殊值替换为 0 df['财富值变化'] = df['财富值变化'].replace('NEW', ...
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?
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....
一、前言二、本文概要三、pandas merge by 修罗闪空3.1 merge函数用途3.2 merge函数的具体参数3.3 merge函数的应用四、pandas apply by pluto、乔瞧4.1 pandas apply by pluto4.2 pandas apply by 乔瞧pandas pivot_table by 石墨锡 一、前言 本文来自四位读者的合作,这四位读者是之前推文14个pandas神操作,手把手...