随笔分类 - pandas
摘要：import pandas as pd import datacompy #导入datafcompy库 比较两个dataframe之间的区别 #同时也可以比较两个txt之间的区别 df1 = pd.read_csv("1.txt",header=None) df2 = pd.read_csv("22
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摘要：import pandas as pd import matplotlib.pyplot as plt dataflair = pd.read_csv("https://download.mlcc.google.com/mledu-datasets/california_housing_train.
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摘要：import pandas as pd import numpy as np df1= pd.DataFrame({'第一列':[111,222,333,444,555,666],'第二列':[11,22,33,44,55,66],'第三列':['shu1','shun2','shun3','shu
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摘要：import pandas as pd def adder(el1,el2): return el1+el2 def delte(args): return args+"+delte" s1 = pd.Series([1,2,3]) s1 = s1.pipe(adder,3) print(s1) s
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摘要：循环路径下的文件将所有的txt文件进行合并 from xlutils.copy import copy import xlrd # 加载已存在的xls old_workbook = xlrd.open_workbook('guoshun.xlsx') # 将已存在的excel拷贝进新的excel n
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摘要：from xlutils.copy import copy import xlrd # 加载已存在的xls old_workbook = xlrd.open_workbook('guoshun.xlsx') # 将已存在的excel拷贝进新的excel new_workbook = copy(old
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摘要：import pandas as pd df=pd.DataFrame({'A':[1,2,3],"B":[11,22,33]}) df['C']=df['A'].apply(lambda x : x+3)#apply运用于series的每个元素，对series运用apply就是对series的每一
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摘要：#利用pandas处理excel文件import pandas as pddf=pd.read_excel('D:\\python.xlsx',sheet_name=0,header=None)#默认是忽略表头的，但是为了让下面的代码读取表头，设置header=None#print(df.head(
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