更改 Pandas 中系列的索引顺序

假设我们想改变系列的索引顺序，那么我们必须使用 pandas 模块的Series.reindex()方法来执行这个任务。

Series ，它是一个能够保存任何数据的一维标记数组。

Syntax: pandas.Series(data, index, dtype, copy)
 

Parameters:

• data takes ndarrys, list, constants.
• index values.
• dtypes for data types.
• Copy data, default is False.

要了解更多关于熊猫系列的信息，请单击此处。

Series.reindex()方法 用于根据索引更改数据。

Syntax: Series.reindex(labels=None, index=None, columns=None, axis=None, method=None, copy=True, level=None, fill_value=nan, limit=None, tolerance=None)
 

要了解有关 pandas Series.reindex() 方法的更多信息，请单击此处。

让我们创建一个系列：

Python3

# import required library
import pandas as pd
import numpy as np
 
# create numpy array
data = np.array(["Android dev",
                 "content writing",
                 "competitive coding"])
#create a series
total_series = pd.Series(data,
                         index = [1, 2, 3])
 
# show the series
total_series

输出：

系列

示例 1：

Python3

# import required library
import pandas as pd
import numpy as np
 
# create numpy array
data = np.array(["Android dev",
                 "content writing",
                 "competitive coding"])
# create a series
total_series = pd.Series(data,
                         index = [1, 2, 3])
# reindexing of series
total_series = total_series.reindex(index
                                    = [3, 2, 1])
# show the series
total_series

输出：

示例 2：

Python3

# import required library
import pandas as pd
import numpy as np
 
# create numpy array
data = np.array(["Android dev",
                 "content writing",
                 "competitive coding"])
# create a series
total_series = pd.Series(data,
                         index = [1, 2, 3])
# reindexing of series
total_series = total_series.reindex([2, 3, 1])
 
# show the series
total_series

输出：