使用Series.map()可以很容易做到,最少仅需一行代码。 #①使用字典进行映射data["gender"] = data["gender"].map({"男":1, "女":0})#②使用函数defgender_map(x): gender = 1if x == "男"else0return gender#注意这里传入的是函数名,不带括号data["gender"] = data["gender"].map(gender_map)...
通过df.set_axis()方法来设置 DataFrame 的 columns import pandas as pd #从 csv 文件读取数据 df = pd.read_csv('data.csv') # 将列名替换为新列名列表 new_columns = ['new_col1', 'new_col2', 'new_col3'] df.set_axis(new_columns, axis='columns', inplace=True) 其中,set_axis() 方法...
() 执行步骤:将数据按照size进行分组在分组内进行聚合操作 grouping multiple columns dogs.groupby...(['type', 'size']) groupby + multi aggregation (dogs .sort_values('size') .groupby('size')['height...values='price') melting dogs.melt() pivoting dogs.pivot(index='size', columns='kids'...
map操作 代码语言:python 代码运行次数:0 运行 AI代码解释 """apply and map examples""" """add 1 to every element""" df.applymap(lambda x: x+1) 第3行+2 代码语言:python 代码运行次数:0 运行 AI代码解释 """add 2 to row 3 and return the series""" df.apply(lambda x: x[3]+2,axi...
#A single group can be selected using get_group():grouped.get_group("bar")#Out:ABC D1barone0.2541611.5117633barthree0.215897-0.9905825bartwo -0.0771181.211526Orfor an object grouped onmultiplecolumns:#for an object grouped on multiple columns:df.groupby(["A","B"]).get_group(("bar","one...
df=pd.DataFrame(rng.random((1000,3)),columns=['A','B','C'])result1=(df['A']+df['B'...
Here are just a few of the things that pandas does well:- Easy handling of missing data in floating point as well as non-floatingpoint data.- Size mutability: columns can be inserted and deleted from DataFrame andhigher dimensional objects- Automatic and explicit data alignment: objects can ...
columns同index inplace:True|False:是否替换原先的df 另一种方式: df.index|columns = [ 列表] #直接替换为一个列表,列表长度与索引长度一致 df.index|columns = df.index|columns.map(Function) #对索引值使用函数进行转换 二、离散数据分组 1、普通分组:cut cats = pd.cut(x, bins, right=True, labels...
Sort columns by multiple variables Using Pandas to Sort by Rows Pandas Sort Values Interactive Example Further Learning Finding interesting bits of data in a DataFrame is often easier if you change the rows' order. You can sort the rows by passing a column name to .sort_values(). In cases...
I'm doing a groupby followed by aggregate, with a dictionary argument. My DataFrame has got duplicated column names, but none of the operations I'm using refer to the duplicate columns. I get this error: File "JetBrains/PyCharm2023.1/scratches/scratch_223.py", line 18, in <module> df....