To use a list to filter a Pandas DataFrame we can make use of the isin function and pass a list of values to keep. In the example below we pass a list called "values" containing the two values from the Embarked column in our DataFrame that we want to filter for. ...
import pandas as pd df = pd.DataFrame({'A': , 'B': , 'C': }) filtered_df = df.filter(like='A', axis=1) print(filtered_df) ``` 使用正则表达式过滤列名(使用regex参数)```python import pandas as pd df = pd.DataFrame({'A': , 'B': , 'C': }) filtered_df = df.filter(r...
data={'Name':['Tom','Nick','John','Tom'],'Age':[20,21,19,18],'Email':['tom@pandasdataframe.com','nick@pandasdataframe.com','john@pandasdataframe.com','tom@pandasdataframe.com']}df=pd.DataFrame(data,index=['a','b','c','d'])filtered_df=df.filter(items=['a','c'],axis=...
})# 筛选列名中包含 'A' 的列filtered_df = df.filter(like='A', axis=1) print(filtered_df) 3)使用正则表达式过滤列名(使用regex参数) importpandasaspd# 创建示例 DataFramedf = pd.DataFrame({'A': [1,2,3],'B': [4,5,6],'C': [7,8,9] })# 筛选列名以 'B' 或 'C' 结尾的列filt...
Filtering data in Pandas is a critical step for effective data analysis. From logical operators to str accessor to loc and iloc, these are the most common methods to know for filtering data in Pandas.
pandas.DataFrame.filter() 方法用于对 DataFrame 进行子集选择,提供灵活的过滤功能。它可以基于列名、行名(索引)、或者自定义的过滤条件来选择特定的行或列。#pandas #pandas函数 #pandas基 - CJavaPY编程之路于20241205发布在抖音,已经收获了2个喜欢,来抖音,记录美
importpandasaspd data={ "name":["Sally","Mary","John"], "age":[50,40,30], "qualified":[True,False,False] } df=pd.DataFrame(data) newdf=df.filter(items=["name","age"]) print(newdf) 运行一下 定义与用法 filter()方法筛选 DataFrame ,并仅返回在筛选器中指定的行或列。
PandasDataFrame.filter(~)方法返回标签与指定模式匹配的行或列。 警告 该方法根据列/行的标签而不是实际数据应用过滤。 参数 1.items|list-like|optional 提取items中包含标签的行或列。 2.like|string|optional 提取标签包含like的行或列。 3.regex|string(正则表达式)|optional ...
loc is an abbreviation of location term. All these 3 methods return same output. It's just a different ways of doing filtering rows. newdf = df.loc[(df.origin == "JFK") & (df.carrier == "B6")] Filter Pandas Dataframe by Row and Column Position ...
A boolean vector is used to filter data in boolean indexing. Parenthesis can be used to group several conditions involving the operators, such as|(OR),&(AND),==(EQUAL), and~(NOT). Filter Data in a Pandas DataFrame Based on Single Condition ...