《Python数据分析技术栈》第06章使用 Pandas 准备数据 02 pandas的组件（Building blocks of Pandas）
The Series and DataFrame objects are the underlying data structures in Pandas. In a nutshell, a Series is like a column (has only one dimension), and a DataFrame (has two dimensions ) is like a table or a spreadsheet with rows and columns. Each value stored in a Series or a DataFrame has a label or an index attached to it, which speeds up retrieval and access to data. In this section, we learn how to create a Series and DataFrame, and the functions used for manipulating these objects.
系列（Series）和数据帧（DataFrame）对象是 Pandas 的底层数据结构。简而言之，Series 就像一列（只有一个维度），而 DataFrame（有两个维度）就像一个有行和列的表格或电子表格。存储在系列或 DataFrame 中的每个值都附有标签或索引，这可以加快数据检索和访问速度。在本节中，我们将学习如何创建系列和数据帧，以及用于操作这些对象的函数。
The Series is a one-dimensional object, with a set of values and their associated indexes. Table 6-1 lists the different ways of creating a series.
系列是一个一维对象，包含一组值及其相关索引。表 6-1 列出了创建系列的不同方法。
Using a scalar value：
使用标量值：
pd.Series(2)
#Creating a simple series with just one value. Here, 0 is the index label, and 2 is the value the Series object contains.
Using a list：
pd.Series([2]*5)
#Creating a series by enclosing a single value (2) in a list and replicating it 5 times. 0,1,2,3,4 are the autogenerated index labels.
Using characters in a string:
pd.Series(list('hello'))
#Creating a series by using each character in the string "hello" as a separate value in the Series.
Using a dictionary:
pd.Series({1:'India',2:'Japan',3:'Singapore'})
#The key/value pairs correspond to the index labels and values in the Series object.
Using a range:
pd.Series(np.arange(1,5))
#Using the NumPy arrange function to create a series from a range of 4 numbers (1-4), ensure that the NumPy library is also imported
Using random numbers:
pd.Series(np.random.normal(size=4))
#Creating a set of 4 random numbers using the np.random.normal function
Creating a series with customized index labels:
pd.Series([2,0,1,6],index=['a','b','c','d'])
#The list [2,0,1,6] specifies the values in the series, and the list for the index['a','b','c','d'] specifies the index labels
To summarize, you can create a Series object from a single (scalar) value, list, dictionary, a set of random numbers, or a range of numbers. The pd.Series function creates a Series object (note that the letter “S” in “Series” is in uppercase; pd.series will not work). Use the index parameter if you want to customize the index.
简而言之，您可以通过单个（标量）值、列表、字典、随机数集或数字范围创建 Series 对象。函数 pd.Series 将创建一个 Series 对象（注意，"Series "中的字母 "S "是大写字母；pd.series 将不起作用）。如果要自定义索引，请使用索引参数。