使用Python修改csv中的特定列
我在使用Python修改csv中的特定列,python,csv,Python,Csv,我在.csv中有一组数据,如下所示: -959.378170,-0.000026,-94.960000,1508.000000,9.000000, -958.978170,-0.000026,-94.920000,1508.000000,9.000000, -958.578170,-0.000026,-94.880000,1508.000000,10.000000, -958.178170,-0.000026,-94.840000,1508.000000,10.000000, -957.7781
.csv
中有一组数据,如下所示:
-959.378170,-0.000026,-94.960000,1508.000000,9.000000,
-958.978170,-0.000026,-94.920000,1508.000000,9.000000,
-958.578170,-0.000026,-94.880000,1508.000000,10.000000,
-958.178170,-0.000026,-94.840000,1508.000000,10.000000,
-957.778170,-0.000026,-94.800000,1508.000000,10.000000,
最后两列应该是时间<代码>15是小时,08是分钟,6是秒。最终目标是加入他们,这样我就可以得到:
-958.978170,-0.000026,-94.920000,15:08:09,
-958.578170,-0.000026,-94.880000,15:08:10,
如何执行此操作?使用csv
模块读取.csv
文件(请参见示例),以及将两列解析为datetime
对象的方法,然后您可以将其写入任何您想要的格式(使用datetime.strftime
)
有关更多详细信息,请参见datetime
文档的一节。我将使用和
在示例上运行此操作将导致
-959.378170,-0.000026,-94.960000,15:08:09,
-958.978170,-0.000026,-94.920000,15:08:09,
-958.578170,-0.000026,-94.880000,15:08:10,
-958.178170,-0.000026,-94.840000,15:08:10,
-957.778170,-0.000026,-94.800000,15:08:10,
查看pandas中的read_csv()方法(http://pandas.pydata.org/pandas-docs/stable/io.html#csv-文本文件)
它有一个很棒的日期解析实用程序,允许您将多个列中的字符串组合在一起。python教程是一个很好的开始。然后看看csv和datetime模块。
-959.378170,-0.000026,-94.960000,15:08:09,
-958.978170,-0.000026,-94.920000,15:08:09,
-958.578170,-0.000026,-94.880000,15:08:10,
-958.178170,-0.000026,-94.840000,15:08:10,
-957.778170,-0.000026,-94.800000,15:08:10,