What are the common properties of Pandas Series objects?

The attributes of the Series object are: 1. The index attribute, to view the index of the Series object; 2. The size attribute, to view the number of elements in the Series; 3. The values ​​attribute, to convert the data format in Pandas to Numpy The form of the array; 4. dtype attribute; 5. name attribute.

Common properties of Pandas Series objects:

To view the related properties of Series, you can view Or change the type and index of the sequence elements.

In [1]: import pandas as pd
In [2]: a=pd.Series([0,1,2,3,4,5])

1) The index attribute

The index attribute can view the index of the Series object, and can also be directly assigned and changed. We use .loc and .iloc to modify the index, and do the same processing before and after. Please understand the difference between loc and i loc. The code is as follows.

In [3]: a.index
Out[3]: RangeIndex(start=0, stop=6, step=1)
In [4]: a.loc[1]
Out[4]: 1
In [5]: a.iloc[1]
Out[5]: 1

The index of a is changed. At this time, loc[1] takes the value of the second last position, while iloc[1] still takes the value of the absolute position 1.

In [6]: a.index = [5,4,3,2,1,0]
In [7]: a.index
Out[7]: Int64Index([5, 4, 3, 2, 1, 0], dtype='int64')
In [8]: a.loc[1]
Out[8]: 4
In [9]: a.iloc[1]
Out[9]: 1

2) size attribute

The size attribute can be used to view the number of elements in the Series.

In [10]: a.size  # 查看数据的个数
Out[10]: 6

3) values ​​attribute

The values ​​attribute can be used as a bridge between Pandas and Numpy. The data format in Pandas can be converted to The form of arrays in Numpy.

In [11]: a.values  # 查看返回值，返回的是一个Numpy中的array类型
Out[11]: array([0, 1, 2, 3, 4, 5], dtype=int64)

4) dtype attribute

The dtype attribute is used to view the type of data, and then the data type can be changed through the astype method. Pandas supports many data types, and we need to choose different data types according to different usage scenarios.

In [12]: a.dtype  # 查看数据类型
Out[12]: dtype('int64')
In [13]: a=a.astype('float64')
In [14]: a.dtype  # 查看数据类型

5) name attribute

Get the name of values ​​

6) index.name attribute

Get the name of the index

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