⽤⼆维列表构造原始数据
1import pandas as pd
2
3 data = [['li', 'math', 100], ['bob', 'pe', 99], ['sar', 'english', 98], ['li', 'pe', 89]]
将数据转换成DataFrame类型
1import pandas as pd
2
groupby分组
3 dataFrame = pd.DataFrame(dada, columns = ['name', 'course', 'score']) # columns 为列名并且必须是list类型
打印dataFrame对象
此时不能根据⾏号索引，但是可以根据列名索引
1import pandas as pd
2
3print(dataFrame[0])
1import pandas as pd
2
3print(dataFrame["name"])
此时的dataFrame["name"] 是⼀个类似于⼀维数组的series对象，可根据下标索引
1import pandas as pd
2
3print(dataFrame["name"])
4 print(type(dataFrame["name"]))
5 print(dataFrame["name"][0])
像字典⼀样⽤索引创建新列 dataFrame["age"]
1import pandas as pd
2
3 dataFrame["age"] = [23, 24, 25, 23]
4print(dataFrame)
重点来了，upby("name")根据name属性分组，name列数据项默认成为索引
1import pandas as pd
2
3 dataFrame = upby(["name", "course"])["score"].sum() # 可以通过as_index指定分组项要不要成为索引，默认为True 4print(dataFrame)
5 print(dataFrame["li"])