最后,我们打印了删除前后的DataFrame以进行验证。 请注意,由于inplace=False(这是drop方法的默认行为),上述代码将返回一个新的DataFrame,而不会修改原始DataFrame。如果你希望在原地修改DataFrame,可以将inplace参数设置为True: python df.drop(columns=df.columns[last_second_column_index], inplace=True) 这样,原始DataFrame df 将被直接修改,而不需要将结果重...
我们还可以使用Pandas的drop()方法删除DataFrame中的列名行。该方法可以接受一个整数或字符串列表作为行索引,并返回删除指定行后的新DataFrame。我们可以通过指定axis参数来删除列名行。 以下是一个示例: importpandasaspd# 创建DataFramedf=pd.DataFrame({'姓名':['张三','李四','王五'],'年龄':[18,19,...
In the below example we drop the ‘age‘ column from the DataFrame usingdf.drop(columns = 'col_name') importpandasaspd student_dict = {"name": ["Joe","Nat"],"age": [20,21],"marks": [85.10,77.80]}# Create DataFrame from dictstudent_df = pd.DataFrame(student_dict) print(student_...
import pandas as pdstudent_dict = {'name': ['John','Alex'],'age': [24, 18],'marks': [68.44, 85.67]}# Create DataFrame from dictstudent_df = pd.DataFrame(student_dict)print(student_df.columns.values)# find position of the last column and droppos = len(student_df.columns) - 1st...
Given a Pandas DataFrame, we have to delete the last row of data of it. By Pranit Sharma Last updated : September 22, 2023 Rows in pandas are the different cell (column) values that are aligned horizontally and also provide uniformity. Each row can have the same or different value. ...
DataFrame.drop( labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors="raise", ) Different parameters that can be used for dropping rows and columns are below.label - refers to the name of a row or column. axis - mostly integer or string value that begins ...
It’s crucial to specify whether to drop rows based on index labels or positions, utilizing appropriate parameters such aslabelsorindex. 1. Create a Sample DataFrame Let’s create a pandas DataFrame to explain how to remove the list of rows with examples, my DataFrame contains the column names...
df.drop(df.columns[i], axis=1) Run Code Online (Sandbox Code Playgroud) 如果您在列中有重复的名称,它可能会很奇怪,因此,为此,您可以按名称重命名要删除列的列.或者您可以像这样重新分配DataFrame: df = df.iloc[:, [j for j, c in enumerate(df.columns) if j != i]] Run Code Online (...
DataFrame(mydata) df # 输出 Column1 Column2 0 1 a 1 2 b 2 3 c 指定行索引: # 指定行索引 df.index = ['row1', 'row2', 'row3'] df # 输出 Column1 Column2 row1 1 a row2 2 b row3 3 c 使用另一个 Series 或数组作为索引: # 使用另一个 Series 或数组作为索引 index_series ...
金融数据dataframe,按值排序后重置索引再存储。 data.sort_values(["A","B"]).reset_index(drop=True) feather feather读写速度一流,在空间充足的情况下首选,在小于3GB的DataFrame情况下优势显著。适合, 内存占用小于3GB的DataFrame文件 磁盘空间十分充足。 不必支持分布式计算 pd.read_feather() parquet parquet读...