大熊貓read_csv：頁眉/ skiprows不工作

Question

清一色

第一次問一個問題在這裏，如果道歉格式是壞的，請讓我知道如何改進我的問題。

我在尋求更好的理解pandas.read_csv（）函數的頭文件和skiprows參數。

這裏是原始數據，我想在python閱讀的例子：

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,"" 

我試圖爲使用該行以「日期」或「MMDDYY」爲開頭的行開始我標題行。當我在文本編輯器中打開原始數據時，對應於「Date」的行是第14行，它將是零索引python land中的第13行。

我用下面的代碼認爲它應該跳過第12行，並開始對13進行行讀取數據：

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

但產生錯誤：

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

很多後我發現下面的代碼產生了我之後的結果類型，但是我不明白它爲什麼有效：

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

我不明白read_csv是如何計算行數的。我是不正確的，因爲標題行不在第11行，而是在第13行？該代碼只適用於如果skiprows = [14]，爲什麼呢？

在附註中，是否有辦法阻止原始數據中存在的空白列被讀入數據框？

Answer 1

首先，skiprows沒有做你認爲它在這裏。當你給它一個列表作爲輸入時，它會在解析文件時跳過這些行。對於你想要的，只需使用header。

二，熊貓對文件行進行零索引。

第三，當您有skip_blank_lines=True時，它會在考慮＃header＃值之前重新索引文件的行。因此，在您的示例中，它不會在您的標題（和標題之後的那一行）之前爲空行11和12編制索引。記住大熊貓零的索引文件的行，我們可以看到在標題header=11線燮如何：

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,""