随笔分类 -  dataframe相关

摘要:https://www.jb51.net/article/188649.htm 阅读全文
posted @ 2022-11-22 09:35 Marklong 阅读(37) 评论(0) 推荐(0)
摘要:column_names = res_df.columns.values column_names[3] = '累计收益_1' res_df.columns = column_names 阅读全文
posted @ 2022-11-17 10:55 Marklong 阅读(40) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/weixin_46599926/article/details/122367665 阅读全文
posted @ 2022-11-17 10:53 Marklong 阅读(32) 评论(0) 推荐(0)
摘要:import matplotlib.pyplot as plt 新老分数的密度图 data_score = data[['old_score','new_score']] data_score.plot(kind="kde",color=['lightcoral','lightslategrey'] 阅读全文
posted @ 2022-11-04 15:34 Marklong 阅读(82) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/weixin_39450145/article/details/120795055 阅读全文
posted @ 2022-11-04 15:33 Marklong 阅读(26) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/weixin_46599926/article/details/122852950 阅读全文
posted @ 2022-09-25 17:16 Marklong 阅读(16) 评论(0) 推荐(0)
摘要:https://www.freesion.com/article/4199460039/ 阅读全文
posted @ 2022-09-25 17:16 Marklong 阅读(80) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/weixin_43790276/article/details/125963758 阅读全文
posted @ 2022-09-25 17:16 Marklong 阅读(55) 评论(0) 推荐(0)
摘要:https://blog.51cto.com/u_12136715/2953315 阅读全文
posted @ 2022-09-25 17:12 Marklong 阅读(274) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/qq_52534495/article/details/119850873 阅读全文
posted @ 2022-09-25 17:12 Marklong 阅读(23) 评论(0) 推荐(0)
摘要:https://www.cnblogs.com/Zshirly/p/15854951.html 阅读全文
posted @ 2022-09-25 17:10 Marklong 阅读(34) 评论(0) 推荐(0)
摘要:https://www.zhihu.com/search?type=content&q=Pandas%E8%81%9A%E5%90%88%E6%97%B6%E9%97%B4%E5%BA%8F%E5%88%97%E6%95%B0%E6%8D%AE 注意以下的聚合是从当前时间点往后一段时间计算的。 tm 阅读全文
posted @ 2022-09-25 17:10 Marklong 阅读(132) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/Unravel_36/article/details/123873694 阅读全文
posted @ 2022-09-25 17:09 Marklong 阅读(12) 评论(0) 推荐(0)
摘要:res_df_groupby.dropna(axis=0,how='any') 阅读全文
posted @ 2022-09-25 16:15 Marklong 阅读(16) 评论(0) 推荐(0)
摘要:l=[False,True] tf_lists = [list(i) for i in itertools.product(l,repeat=6)] for i in permutations(cols, len(cols)): for j in i: sort_by.append(j) ori_d 阅读全文
posted @ 2022-09-25 16:13 Marklong 阅读(26) 评论(0) 推荐(0)
摘要:datetime模块中的方法weekday()可用于检索星期几,结果返回0-6之间的整数,用来代表“星期一”到“星期日”。 datetime.date(2022, 2, 22).weekday() 阅读全文
posted @ 2022-09-25 16:11 Marklong 阅读(235) 评论(0) 推荐(0)
摘要:ori_data.loc[:, ["收益"]] = (ori_data .loc[:, ["收益"]] .replace(r"%","", regex=True) .apply(pd.to_numeric, errors="coerce") .div(100) ) 阅读全文
posted @ 2022-09-25 16:09 Marklong 阅读(280) 评论(0) 推荐(0)
摘要:https://blog.csdn.net/qq_53817374/article/details/122974100 阅读全文
posted @ 2022-09-06 15:20 Marklong 阅读(16) 评论(0) 推荐(0)
摘要:https://www.csdn.net/tags/MtTaYgzsMzc0NTQtYmxvZwO0O0OO0O0O.html 阅读全文
posted @ 2022-09-01 10:16 Marklong 阅读(13) 评论(0) 推荐(0)
摘要:https://www.yisu.com/zixun/357302.html 阅读全文
posted @ 2022-09-01 10:15 Marklong 阅读(29) 评论(0) 推荐(0)