大熊猫read_csv：页眉/ skiprows不工作

Question

清一色

第一次问一个问题在这里，如果道歉格式是坏的，请让我知道如何改进我的问题。

我在寻求更好的理解pandas.read_csv（）函数的头文件和skiprows参数。

这里是原始数据，我想在python阅读的例子：

MiniSonde 5 43656 
"Log File Name : lwrhyp_deploy_20170104" 
"Setup Date (MMDDYY) : 010417" 
"Setup Time (HHMMSS) : 114539" 
"Starting Date (MMDDYY) : 010417" 
"Starting Time (HHMMSS) : 140000" 
"Stopping Date (MMDDYY) : 123169" 
"Stopping Time (HHMMSS) : 235959" 
"Interval (HHMMSS) : 010000" 
"Sensor warmup (HHMMSS) : 000100" 
"Circltr warmup (HHMMSS) : 000030" 


"Date","Time","","Temp","","SpCond","","Sal","","Dep25","","TDG","","TDG","","LDO%","","LDO","","IBatt","" 
"MMDDYY","HHMMSS","","øC","","mS/cm","","ppt","","meters","","mmHg","","psia","","Sat","","mg/l","","Volts","" 

01/04/17,14:00:00,"",7.97,"",.0691,"",.02,"",.75,"",735,"",14.22,"",52.7,"",6.15,"",11.4,"" 
01/04/17,15:00:00,"",7.9,"",.0692,"",.02,"",.76,"",736,"",14.23,"",52.8,"",6.17,"",11.4,"" 
01/04/17,16:00:00,"",7.89,"",.0694,"",.02,"",.77,"",736,"",14.23,"",52.3,"",6.12,"",11.4,"" 
01/04/17,17:00:00,"",7.88,"",.0699,"",.02,"",.78,"",735,"",14.21,"",51.8,"",6.06,"",11.4,"" 
01/04/17,18:00:00,"",7.85,"",.0699,"",.02,"",.78,"",733,"",14.18,"",51.3,"",6.01,"",11.4,"" 
01/04/17,19:00:00,"",7.83,"",.0706,"",.02,"",.78,"",731,"",14.14,"",51.3,"",6.01,"",11.4,"" 
01/04/17,20:00:00,"",7.81,"",.0706,"",.02,"",.79,"",730,"",14.12,"",51.1,"",5.99,"",11.4,"" 
01/04/17,21:00:00,"",7.81,"",.0699,"",.02,"",.79,"",730,"",14.11,"",50.8,"",5.95,"",11.4,"" 
01/04/17,22:00:00,"",7.76,"",.0702,"",.02,"",.8,"",729,"",14.1,"",50.5,"",5.92,"",11.3,"" 
01/04/17,23:00:00,"",7.76,"",.0704,"",.02,"",.8,"",729,"",14.09,"",50.5,"",5.93,"",11.3,"" 
01/05/17,00:00:00,"",7.76,"",.07,"",.02,"",.8,"",729,"",14.09,"",50.5,"",5.92,"",11.3,"" 

我试图为使用该行以“日期”或“MMDDYY”为开头的行开始我标题行。当我在文本编辑器中打开原始数据时，对应于“Date”的行是第14行，它将是零索引python land中的第13行。

我用下面的代码认为它应该跳过第12行，并开始对13进行行读取数据：

test = pd.read_csv(filepath, skiprows=12, skip_blank_lines=True) 

但产生错误：

UnicodeDecodeError: 'utf-8' codec can't decode byte 0xf8 in position 0: invalid start byte 

很多后我发现下面的代码产生了我之后的结果类型，但是我不明白它为什么有效：

test = pd.read_csv(filepath, skiprows=[14], header=11, skip_blank_lines=True) 

我不明白read_csv是如何计算行数的。我是不正确的，因为标题行不在第11行，而是在第13行？该代码只适用于如果skiprows = [14]，为什么呢？

在附注中，是否有办法阻止原始数据中存在的空白列被读入数据框？

Answer 1

首先，skiprows没有做你认为它在这里。当你给它一个列表作为输入时，它会在解析文件时跳过这些行。对于你想要的，只需使用header。

二，熊猫对文件行进行零索引。

第三，当您有skip_blank_lines=True时，它会在考虑＃header＃值之前重新索引文件的行。因此，在您的示例中，它不会在您的标题（和标题之后的那一行）之前为空行11和12编制索引。记住大熊猫零的索引文件的行，我们可以看到在标题header=11线燮如何：

line/ : content 
0:MiniSonde 5 43656 
1:"Log File Name : lwrhyp_deploy_20170104" 
2:"Setup Date (MMDDYY) : 010417" 
3:"Setup Time (HHMMSS) : 114539" 
4:"Starting Date (MMDDYY) : 010417" 
5:"Starting Time (HHMMSS) : 140000" 
6:"Stopping Date (MMDDYY) : 123169" 
7:"Stopping Time (HHMMSS) : 235959" 
8:"Interval (HHMMSS) : 010000" 
9:"Sensor warmup (HHMMSS) : 000100" 
10:"Circltr warmup (HHMMSS) : 000030" 


11:"Date","Time","","Temp","","SpCond","","Sal","","Dep25","","TDG","","TDG","","LDO%","","LDO","","IBatt","" 
12:"MMDDYY","HHMMSS","","øC","","mS/cm","","ppt","","meters","","mmHg","","psia","","Sat","","mg/l","","Volts","" 

13:01/04/17,14:00:00,"",7.97,"",.0691,"",.02,"",.75,"",735,"",14.22,"",52.7,"",6.15,"",11.4,"" 
14:01/04/17,15:00:00,"",7.9,"",.0692,"",.02,"",.76,"",736,"",14.23,"",52.8,"",6.17,"",11.4,"" 
15:01/04/17,16:00:00,"",7.89,"",.0694,"",.02,"",.77,"",736,"",14.23,"",52.3,"",6.12,"",11.4,"" 
16:01/04/17,17:00:00,"",7.88,"",.0699,"",.02,"",.78,"",735,"",14.21,"",51.8,"",6.06,"",11.4,"" 
17:01/04/17,18:00:00,"",7.85,"",.0699,"",.02,"",.78,"",733,"",14.18,"",51.3,"",6.01,"",11.4,"" 
18:01/04/17,19:00:00,"",7.83,"",.0706,"",.02,"",.78,"",731,"",14.14,"",51.3,"",6.01,"",11.4,"" 
19:01/04/17,20:00:00,"",7.81,"",.0706,"",.02,"",.79,"",730,"",14.12,"",51.1,"",5.99,"",11.4,"" 
20:01/04/17,21:00:00,"",7.81,"",.0699,"",.02,"",.79,"",730,"",14.11,"",50.8,"",5.95,"",11.4,"" 
21:01/04/17,22:00:00,"",7.76,"",.0702,"",.02,"",.8,"",729,"",14.1,"",50.5,"",5.92,"",11.3,"" 
22:01/04/17,23:00:00,"",7.76,"",.0704,"",.02,"",.8,"",729,"",14.09,"",50.5,"",5.93,"",11.3,"" 
23:01/05/17,00:00:00,"",7.76,"",.07,"",.02,"",.8,"",729,"",14.09,"",50.5,"",5.92,"",11.3,""