![](https://img.haomeiwen.com/i27364451/a14a457638ebd577.png)
![](https://img.haomeiwen.com/i27364451/03a32557198990a8.png)
df=pd.DataFrame({"team":["A","B","B","A","A","C","C"],
"name":["Adne","Atlin","Fis","WangF","Dange","Dad","Eas"],
"Q1":[50,75,26,31,75,78,89],
"Q2":[70,65,96,38,85,50,60],
"Q3":[90,85,36,66,70,80,40],
"Q4":[70,35,60,20,55,90,90]})
df
![](https://img.haomeiwen.com/i27364451/76d3a0d38ae27da6.png)
1DataFrame的数据选择
1.1行的选择
1.1.1 df.index的使用
![](https://img.haomeiwen.com/i27364451/9614299272e3832d.png)
![](https://img.haomeiwen.com/i27364451/841bca285f321cde.png)
![](https://img.haomeiwen.com/i27364451/48d4d43f1a93a2bb.png)
![](https://img.haomeiwen.com/i27364451/7ff9dd4f2fe371da.png)
1.1.2 切片符在行的使用
![](https://img.haomeiwen.com/i27364451/68d61cdda6443b07.png)
1.1.3 函数在行的使用
![](https://img.haomeiwen.com/i27364451/2173bbf68e5b0eaf.png)
![](https://img.haomeiwen.com/i27364451/c5f02940a9312899.png)
![](https://img.haomeiwen.com/i27364451/6797e95aec3e6964.png)
![](https://img.haomeiwen.com/i27364451/d3ceed018074cbcb.png)
![](https://img.haomeiwen.com/i27364451/cd56c68e57cf2406.png)
![](https://img.haomeiwen.com/i27364451/84d7e5f5b5aaea4d.png)
![](https://img.haomeiwen.com/i27364451/098628a2d52dd388.png)
![](https://img.haomeiwen.com/i27364451/3cf70d99a4c83c2f.png)
1.2 列数据的选择
1.2.1 df.columns在列的选择
![](https://img.haomeiwen.com/i27364451/f16de486e37f488d.png)
![](https://img.haomeiwen.com/i27364451/5e0b5e244d8888be.png)
![](https://img.haomeiwen.com/i27364451/875d78badf08dc3d.png)
![](https://img.haomeiwen.com/i27364451/477c5b7ff26a6221.png)
1.2.2 切片符在列的使用
![](https://img.haomeiwen.com/i27364451/cfdf6487100c7a53.png)
![](https://img.haomeiwen.com/i27364451/92a4dc5b2af2e87d.png)
![](https://img.haomeiwen.com/i27364451/970e5e90ba0dcc75.png)
![](https://img.haomeiwen.com/i27364451/520b015b6416ac1f.png)
![](https://img.haomeiwen.com/i27364451/03e25797a110c65b.png)
![](https://img.haomeiwen.com/i27364451/3a942382717ae4b0.png)
![](https://img.haomeiwen.com/i27364451/1978926d70df92aa.png)
![](https://img.haomeiwen.com/i27364451/2ba2c538ab9ad2ab.png)
![](https://img.haomeiwen.com/i27364451/630b8201ab739840.png)
![](https://img.haomeiwen.com/i27364451/713d10390038e8bf.png)
![](https://img.haomeiwen.com/i27364451/04de9a1ac11a678a.png)
1.2.3 df. 对列的展示
![](https://img.haomeiwen.com/i27364451/5fef4cf6175ed5e1.png)
![](https://img.haomeiwen.com/i27364451/bc71d2d89435f034.png)
![](https://img.haomeiwen.com/i27364451/8e1c3fa55fcaa752.png)
![](https://img.haomeiwen.com/i27364451/4181d5536eb90fc3.png)
![](https://img.haomeiwen.com/i27364451/a75c2ffcc06b90e1.png)
1.3 行和列的同时选择
行和列的同时选择,是上面各种情况的综合运用。
1.4 值的选择
![](https://img.haomeiwen.com/i27364451/b17132b832314b8b.png)
2 Series的数据选择
df1=pd.Series((1,2,3,4,5),
index=[0,1,2,3,4])
df1
![](https://img.haomeiwen.com/i27364451/57a060c84176717c.png)
2.1 切片符的使用
![](https://img.haomeiwen.com/i27364451/dc58dd9f5a9cd4e5.png)
2.2 index方法
![](https://img.haomeiwen.com/i27364451/2dd487627ea06226.png)
2.3 value方法
![](https://img.haomeiwen.com/i27364451/ba4d8666bb23c727.png)
2.4 loc方法或iloc方法
![](https://img.haomeiwen.com/i27364451/40ab80a2313784c2.png)
如果index一致,两个函数是一样使用的
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