通过整数访问行和通过标签 Pandas 访问列
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Access Rows by integers and Columns by labels Pandas
提问by sir_osthara
My data is like this:
我的数据是这样的：
[First row is headers]
[第一行是标题]
Name,Email,Age
Sachith,[email protected],23
Sim,[email protected],234
Yoshi,[email protected],2345
sarla,[email protected],234
I would like to access elements such that rows are specified as integers and columns by labels. i.e for SimI would like to access it as [1,'Name']and so-on
我想访问元素，以便通过标签将行指定为整数和列。即对SIM卡，我想访问它[1，“名称”]等上
My question is should I use locor ix?
我的问题是我应该使用loc还是ix？
Looking at the documentation, I am confused as to what is a pandas index? Is it used to access rows or columns or both? When I try to print the indices of this data, I get a (4,) dtype=int64 array of [0,1,2,3]. So , are columns not part of the index?
查看文档，我对什么是Pandas索引感到困惑？它是用来访问行或列还是两者兼而有之？当我尝试打印这些数据的索引时，我得到一个 [0,1,2,3] 的 (4,) dtype=int64 数组。那么，列不是索引的一部分吗？
回答by jezrael
Use locor iloc, because ixis deprecated.
print (df)
Name Email Age
0 Sachith [email protected] 23
1 Sim [email protected] 234
2 Yoshi [email protected] 2345
3 sarla [email protected] 234
#select by label 1 and label Name
a = df.loc[1, 'Name']
print (a)
Sim
But if need select index by position (need iloc) and columns by labels (need loc) together:
但是如果需要按位置（need iloc）选择索引和按标签（need loc）列选择一起：
df = df.set_index('Email')
print (df)
Name Age
Email
[email protected] Sachith 23
[email protected] Sim 234
[email protected] Yoshi 2345
[email protected] sarla 234
get label of second index by df.index[1]:
通过以下方式获取第二个索引的标签df.index[1]：
a = df.loc[df.index[1], 'Name']
print (a)
Sim
Or get position of label by get_loc:
或通过get_loc以下方式获取标签位置：
a = df.iloc[1, df.columns.get_loc('Name')]
print (a)
Sim
