三、pandas数据分析
1、创建pandas中的Series
(1)从列表中创建
temperature = [33,19,15,89,11,-5,9]
days = ["Mon","Tue","Wed","Thu","Fri","Sat","Sun"]
series_from_list =pd.Series(temperature,days)
series_from_list

(2)从字典中创建
my_dict = {"Mon":33,"Tue":19,"Wed":15,"Thu":89,"Fri":11,"Sat":-5,"Sun":9}
series_from_dict = pd.Series(my_dict)
series_from_dict

(3)从numpy数组中创建
my_array = np.linspace(0,10,15)
series_from_ndarray = pd.Series(my_array)
series_from_ndarray

尚未指定任何索引,pandas将自动生成整数索引,该索引位于0-元素数量减1.
另外还可通过pandas Series执行向量化操作,这与numpy数组类似。如图所示:

2、创建pandas中的DataFrame
Text,CSV,excel文件或数据库
3、pandas操作
data.head()显示前5行数据
data.tail() 显示最后5行数据