pandas DataFrame - V2EX
V2EX = way to explore
V2EX 是一个关于分享和探索的地方
现在注册
已注册用户请  登录
推荐学习书目
Learn Python the Hard Way
Python Sites
PyPI - Python Package Index
http://diveintopython.org/toc/index.html
Pocoo
值得关注的项目
PyPy
Celery
Jinja2
Read the Docs
gevent
pyenv
virtualenv
Stackless Python
Beautiful Soup
结巴中文分词
Green Unicorn
Sentry
Shovel
Pyflakes
pytest
Python 编程
pep8 Checker
Styles
PEP 8
Google Python Style Guide
Code Style from The Hitchhiker's Guide
badacook
V2EX    Python

pandas DataFrame

  •  
  •   badacook 2021-03-26 08:59:00 +08:00 2448 次点击
    这是一个创建于 1660 天前的主题,其中的信息可能已经有所发展或是发生改变。
    列数据
    col1 = pd.Series(['a', 'b'])
    col2 = pd.Series(['x', 'y'])
    col3 = pd.Series(['1', '2'])

    pandas 的 DataFrame
    col1 col2 col3
    a x 1
    a x 2
    a y 1
    a y 2
    b x 1
    b x 2
    b y 1
    b y 2

    想请教一下大家 pandas 能否用 上面的列数据,生成 下面的 DataFrame 二维表,有别于筛选和交、差、并、补,不知道有没有,pandas 直接实现的函数,还望大家不吝赐教,谢谢了
    8 条回复    2021-03-26 15:25:23 +08:00
    a342191555
        1
    a342191555  
       2021-03-26 09:08:45 +08:00 via iPhone
    popil1987
        2
    popil1987  
       2021-03-26 09:10:04 +08:00 via Android
    好像没有,可以用 Python 的 combination 函数
    princelai
        3
    princelai  
       2021-03-26 10:01:06 +08:00
    一楼的方法应该可以,笛卡尔积对应的是 product

    ```
    from itertools import product
    pd.DataFrame(product(col1.to_list(),col2.to_list(),col3.to_list()))
    ```
    yuankui
        4
    yuankui  
       2021-03-26 10:14:49 +08:00
    python 不清楚,java 或者 js 可以用 flatmap
    princelai
        5
    princelai  
       2021-03-26 10:24:18 +08:00
    @princelai #3 哦对了,不引入别的包,只用 pandas 也可以实现,使用 MultiIndex 就行了

    ```
    pd.MultiIndex.from_product([col1.to_list(),col2.to_list(),col3.to_list()]).to_frame(index=None)
    ```
    maloneleo88
        6
    maloneleo88  
       2021-03-26 10:27:54 +08:00 via Android
    借楼问问 openpyxl 怎么附加写入某列,在不知道此列行长度的情况下
    badacook
        7
    badacook  
    OP
       2021-03-26 10:55:33 +08:00
    @a342191555
    @princelai
    非常感谢 两位的指点 非常 nice
    dongxiao
        8
    dongxiao  
       2021-03-26 15:25:23 +08:00
    ```python

    col1 = pd.Series(['a', 'b'])
    col2 = pd.Series(['x', 'y'])
    col3 = pd.Series(['1', '2'])

    col1, col2, col3 = map(pd.DataFrame, [col1, col2, col3])
    col1.index = [1 for _ in range(len(col1))]
    col2.index = [1 for _ in range(len(col2))]
    col3.index = [1 for _ in range(len(col3))]

    r = (
    col1
    .join(col2, how="outer", lsuffix="_col1", rsuffix="_col2")
    .join(col3, how="outer")
    )
    r.columns = ["col1", "col2", "col3"]

    print(r)
    ```
    关于     帮助文档     自助推广系统     博客     API     FAQ     Solana     3996 人在线   最高记录 6679       Select Language
    创意工作者们的社区
    World is powered by solitude
    VERSION: 3.9.8.5 29ms UTC 05:18 PVG 13:18 LAX 22:18 JFK 01:18
    Do have faith in what you're doing.
    ubao snddm index pchome yahoo rakuten mypaper meadowduck bidyahoo youbao zxmzxm asda bnvcg cvbfg dfscv mmhjk xxddc yybgb zznbn ccubao uaitu acv GXCV ET GDG YH FG BCVB FJFH CBRE CBC GDG ET54 WRWR RWER WREW WRWER RWER SDG EW SF DSFSF fbbs ubao fhd dfg ewr dg df ewwr ewwr et ruyut utut dfg fgd gdfgt etg dfgt dfgd ert4 gd fgg wr 235 wer3 we vsdf sdf gdf ert xcv sdf rwer hfd dfg cvb rwf afb dfh jgh bmn lgh rty gfds cxv xcv xcs vdas fdf fgd cv sdf tert sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf sdf shasha9178 shasha9178 shasha9178 shasha9178 shasha9178 liflif2 liflif2 liflif2 liflif2 liflif2 liblib3 liblib3 liblib3 liblib3 liblib3 zhazha444 zhazha444 zhazha444 zhazha444 zhazha444 dende5 dende denden denden2 denden21 fenfen9 fenf619 fen619 fenfe9 fe619 sdf sdf sdf sdf sdf zhazh90 zhazh0 zhaa50 zha90 zh590 zho zhoz zhozh zhozho zhozho2 lislis lls95 lili95 lils5 liss9 sdf0ty987 sdft876 sdft9876 sdf09876 sd0t9876 sdf0ty98 sdf0976 sdf0ty986 sdf0ty96 sdf0t76 sdf0876 df0ty98 sf0t876 sd0ty76 sdy76 sdf76 sdf0t76 sdf0ty9 sdf0ty98 sdf0ty987 sdf0ty98 sdf6676 sdf876 sd876 sd876 sdf6 sdf6 sdf9876 sdf0t sdf06 sdf0ty9776 sdf0ty9776 sdf0ty76 sdf8876 sdf0t sd6 sdf06 s688876 sd688 sdf86