【发布时间】:2020-06-02 04:18:13
【问题描述】:
我正在创建一长串似乎是元组的列表,我想稍后将其转换为 Dataframe,但是某些常见的字符序列阻止了这种情况的发生。以及一小部分输出的示例:
0,"GAME_ID 21900001
EVENTNUM 2
EVENTMSGTYPE 12
EVENTMSGACTIONTYPE 0
PERIOD 1
WCTIMESTRING 8:04 PM
PCTIMESTRING 12:00
HOMEDESCRIPTION
NEUTRALDESCRIPTION
VISITORDESCRIPTION
SCORE NaN
SCOREMARGIN NaN
PERSON1TYPE 0
PLAYER1_ID 0
PLAYER1_NAME NaN
PLAYER1_TEAM_ID NaN
PLAYER1_TEAM_CITY NaN
PLAYER1_TEAM_NICKNAME NaN
PLAYER1_TEAM_ABBREVIATION NaN
PERSON2TYPE 0
PLAYER2_ID 0
PLAYER2_NAME NaN
PLAYER2_TEAM_ID NaN
PLAYER2_TEAM_CITY NaN
PLAYER2_TEAM_NICKNAME NaN
PLAYER2_TEAM_ABBREVIATION NaN
PERSON3TYPE 0
PLAYER3_ID 0
PLAYER3_NAME NaN
PLAYER3_TEAM_ID NaN
PLAYER3_TEAM_CITY NaN
PLAYER3_TEAM_NICKNAME NaN
PLAYER3_TEAM_ABBREVIATION NaN
VIDEO_AVAILABLE_FLAG 0
DESCRIPTION
TIME_ELAPSED 0
TIME_ELAPSED_PERIOD 0
Name: 0, dtype: object"
而期望的输出是:
GAME_ID 21900001
EVENTNUM 2
EVENTMSGTYPE 12
EVENTMSGACTIONTYPE 0
PERIOD 1
WCTIMESTRING 8:04 PM
PCTIMESTRING 12:00
HOMEDESCRIPTION
NEUTRALDESCRIPTION
VISITORDESCRIPTION
SCORE NaN
SCOREMARGIN NaN
PERSON1TYPE 0
PLAYER1_ID 0
PLAYER1_NAME NaN
PLAYER1_TEAM_ID NaN
PLAYER1_TEAM_CITY NaN
PLAYER1_TEAM_NICKNAME NaN
PLAYER1_TEAM_ABBREVIATION NaN
PERSON2TYPE 0
PLAYER2_ID 0
PLAYER2_NAME NaN
PLAYER2_TEAM_ID NaN
PLAYER2_TEAM_CITY NaN
PLAYER2_TEAM_NICKNAME NaN
PLAYER2_TEAM_ABBREVIATION NaN
PERSON3TYPE 0
PLAYER3_ID 0
PLAYER3_NAME NaN
PLAYER3_TEAM_ID NaN
PLAYER3_TEAM_CITY NaN
PLAYER3_TEAM_NICKNAME NaN
PLAYER3_TEAM_ABBREVIATION NaN
VIDEO_AVAILABLE_FLAG 0
DESCRIPTION
TIME_ELAPSED 0
TIME_ELAPSED_PERIOD 0
我怎样才能去掉开头的 0 和 ",然后去掉 TIME_ELAPSED_PERIOD 后面的垃圾?开头的 int 和底行的 int 增加 1 直到我的结尾程序,它可能会超过 320,000,所以我需要代码能够适应一系列 int 值。我认为在创建我的列表之后这样做是最容易的,所以它不应该有必要让我向您展示我的任何代码。只需系统地处理字符就可以了。谢谢!
【问题讨论】:
-
您能否对此进行更多解释:“开始处的 int 和底行中的 int 增加 1 直到我的程序结束,这可能会超过 320,000 左右”。根据您的解释,尚不清楚您的输入数据的类型是什么。它是一个包含几批输入数据的列表,以您解释的格式一个接一个地附加,还是每批输入数据都有单独的列表?
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类似的数据块重复使用相同的行标题(即 PLAYER_3_ID),但每行的数据不同(这是篮球比赛的逐场比赛工作者)。该数据开头的“0”和结尾的“名称:0,dtype:对象”是我要删除的部分。下面的下一个“块”数据将以“1”开头,以“名称:1,dtype:object”结尾,之后的每个块的开头和结尾显示的数字都会加一。无论 x 的值如何,我都想完全删除 'x,"' 和 'Name: x, dtype: object"'。
标签: python pandas dataframe type-conversion tuples