英文:
Importing CSV to r and remove the rows of notes both at begining and middle
问题
我有几个由空气传感器（TSI Bluesky和AirAssure）记录的CSV文件。该设备将数据记录到其SD卡上。与许多由机器记录的文件一样，前59行是以#开头的注释，用于记录基本信息，如序列号。通过添加skip=59可以轻松跳过这些注释。然而，这些注释可能会在CSV文件中间出现，打破了记录。与此同时，列名将再次重复。我有以下示例。
| #note | ||
| #note | ||
| #note | ||
| #note | ||
| col1 | col2 | col3 |
| unit1 | unit2 | unit3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
| #note | ||
| #note | ||
| #note | ||
| #note | ||
| col1 | col2 | col3 |
| unit1 | unit2 | unit3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
如何跳过所有的note和unit，只保留一个列名和所有的数字？
英文:
I have several csv files recorded by air sensor (TSI Bluesky and AirAssure). This device records the data to its SD card. As with many machine-recorded files, the first 59 lines are notes that start with # to record basic information like serial numbers. These notes are easy to skip by adding skip=59. However, these notes could appear in the middle of the csv files by breaking the record. Meanwhile, the column names will repeat again. I have an example below.
| #note | ||
| #note | ||
| #note | ||
| #note | ||
| col1 | col2 | col3 |
| unit1 | unit2 | unit3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
| #note | ||
| #note | ||
| #note | ||
| #note | ||
| col1 | col2 | col3 |
| unit1 | unit2 | unit3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
| 1 | 2 | 3 |
How can I skip all the note and unit and only keep one column name and all the numbers?
答案1
得分: 2
这段代码从文本中读取数据，所以如果你从某个文件夹加载CSV文件，请检查分隔符是否为"\t"或" "。
comment.char 参数用于过滤注释行：#note
text <-"#note#note#note#notecol1 col2 col3unit1 unit2 unit31 2 31 2 31 2 3#note#note#note#notecol1 col2 col3unit1 unit2 unit31 2 31 2 31 2 3"library(dplyr)df <- read.csv(text = text, comment.char = "#", sep = "\t")filter(df, !col1 %in% c('col1', 'unit1'))
输出:
col1 col2 col31 1 1 2 32 2 1 2 33 3 1 2 34 4 1 2 35 5 1 2 36 6 1 2 3
英文:
This code reads data from text, so if you are loading the csv file from some a folder, please check that the separator is "\t" or " "
The comment.char parameter filters the notes: #note
text <-"#note#note#note#notecol1 col2 col3unit1 unit2 unit31 2 31 2 31 2 3#note#note#note#notecol1 col2 col3unit1 unit2 unit31 2 31 2 31 2 3"library(dplyr)df <- read.csv(text = text, comment.char = "#", sep = "\t")filter(df, !col1 %in% c('col1', 'unit1'))
Output:
> col1 col2 col3
> 1 1 2 3
> 2 1 2 3
> 3 1 2 3
> 4 1 2 3
> 5 1 2 3
> 6 1 2 3
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