我有一个大的.csv文件，我需要从中提取信息并将此信息添加到另一列。我的csv看起来像这样：
file_name,#,Date,Time,Temp (°C) ,Intensity
trap12u_10733862_150809.txt,1,05/28/15,06:00:00.0,20.424,215.3,,
trap12u_10733862_150809.txt,2,05/28/15,07:00:00.0,21.091,1,130.2,,
trap12u_10733862_150809.txt,3,05/28/15,08:00:00.0,26.195,3,100.0,,
trap11u_10733862_150809.txt,4,05/28/15,09:00:00.0,25.222,3,444.5,,
trap11u_10733862_150809.txt,5,05/28/15,10:00:00.0,26.195,3,100.0,,
trap11u_10733862_150809.txt,6,05/28/15,11:00:00.0,25.902,2,927.8,,
trap11u_10733862_150809.txt,7,05/28/15,12:00:00.0,25.708,2,325.0,,
trap12c_10733862_150809.txt,8,05/28/15,13:00:00.0,26.292,3,100.0,,
trap12c_10733862_150809.txt,9,05/28/15,14:00:00.0,26.390,2,066.7,,
trap12c_10733862_150809.txt,10,05/28/15,15:00:00.0,26.097,1,463.9,,
我想创建一个包含“file_name”列数据的两个新列。我想在文本“陷阱”之后提取一到两个数字，我想提取c或u并使用此数据创建新列。处理后数据看起来像这样：
file_name,#,Date,Time,Temp (°C) ,Intensity,can_und,trap_no
trap12u_10733862_150809.txt,1,05/28/15,06:00:00.0,20.424,215.3,,u,12
trap12u_10733862_150809.txt,2,05/28/15,07:00:00.0,21.091,1,130.2,,u,12
trap12u_10733862_150809.txt,3,05/28/15,08:00:00.0,26.195,3,100.0,,u,12
trap11u_10733862_150809.txt,4,05/28/15,09:00:00.0,25.222,3,444.5,,u,11
trap12c_10733862_150809.txt,8,05/28/15,13:00:00.0,26.292,3,100.0,,c,12
trap12c_10733862_150809.txt,9,05/28/15,14:00:00.0,26.390,2,066.7,,c,12
trap12c_10733862_150809.txt,10,05/28/15,15:00:00.0,26.097,1,463.9,,c,12
我怀疑这样做的方法是使用awk和正则表达式，但我不确定如何实现正则表达式。如何提取一列的部分并将其附加到其他列？
答案 0 :(得分：3)
使用sed即可：
sed -E '1s/.*/&,can_und,trap_no/; 2,$s/trap([0-9]+)([a-z]).*/&\2,\1/' file.csv
file_name,#,Date,Time,Temp (°C) ,Intensity,can_und,trap_no
trap12u_10733862_150809.txt,1,05/28/15,06:00:00.0,20.424,215.3,,u,12
trap12u_10733862_150809.txt,2,05/28/15,07:00:00.0,21.091,1,130.2,,u,12
trap12u_10733862_150809.txt,3,05/28/15,08:00:00.0,26.195,3,100.0,,u,12
trap11u_10733862_150809.txt,4,05/28/15,09:00:00.0,25.222,3,444.5,,u,11
trap11u_10733862_150809.txt,5,05/28/15,10:00:00.0,26.195,3,100.0,,u,11
trap11u_10733862_150809.txt,6,05/28/15,11:00:00.0,25.902,2,927.8,,u,11
trap11u_10733862_150809.txt,7,05/28/15,12:00:00.0,25.708,2,325.0,,u,11
trap12c_10733862_150809.txt,8,05/28/15,13:00:00.0,26.292,3,100.0,,c,12
trap12c_10733862_150809.txt,9,05/28/15,14:00:00.0,26.390,2,066.7,,c,12
trap12c_10733862_150809.txt,10,05/28/15,15:00:00.0,26.097,1,463.9,,c,12
答案 1 :(得分：1)
使用sed，这将是：
sed 's/trap\([[:digit:]]\+\)\(.\)\(.*\)$/trap\1\2\3\2,\1/' file
使用sed -i ...将其替换为文件。
答案 2 :(得分：1)
gawk 方法：
awk -F, 'NR==1{ print $0,"can_und,trap_no" }
NR>1{ match($1,/^trap([0-9]+)([a-z])/,a); print $0 a[2],a[1] }' OFS="," file
输出：
file_name,#,Date,Time,Temp (°C) ,Intensity,can_und,trap_no
trap12u_10733862_150809.txt,1,05/28/15,06:00:00.0,20.424,215.3,,u,12
trap12u_10733862_150809.txt,2,05/28/15,07:00:00.0,21.091,1,130.2,,u,12
trap12u_10733862_150809.txt,3,05/28/15,08:00:00.0,26.195,3,100.0,,u,12
trap11u_10733862_150809.txt,4,05/28/15,09:00:00.0,25.222,3,444.5,,u,11
trap11u_10733862_150809.txt,5,05/28/15,10:00:00.0,26.195,3,100.0,,u,11
trap11u_10733862_150809.txt,6,05/28/15,11:00:00.0,25.902,2,927.8,,u,11
trap11u_10733862_150809.txt,7,05/28/15,12:00:00.0,25.708,2,325.0,,u,11
trap12c_10733862_150809.txt,8,05/28/15,13:00:00.0,26.292,3,100.0,,c,12
trap12c_10733862_150809.txt,9,05/28/15,14:00:00.0,26.390,2,066.7,,c,12
trap12c_10733862_150809.txt,10,05/28/15,15:00:00.0,26.097,1,463.9,,c,12
NR==1{ print $0,"can_und,trap_no" } - 打印标题行
match($1,/^trap([0-9]+)([a-z])/,a) - 匹配trap字后面的数字和下一个后缀字母
答案 3 :(得分：0)
使用python pandas reader因为python非常适合进行数值分析：
首先：我必须修改数据标题行，以便通过附加3个逗号来保持列的一致性：
file_name，＃，日期，时间，温度（°C），强度,,, 可能有一种方法可以告诉大熊猫忽略列差异 - 但我还是一个菜鸟。
Python代码，用于将数据读入列并创建2个名为“cu_int”和“cu_char”的新列，其中包含文件名的已解析元素：
import pandas
def main():
df = pandas.read_csv("file.csv")
df['cu_int'] = 0 # Add the new columns to the data frame.
df['cu_char'] = ' '
for index, df_row in df.iterrows():
file_name = df['file_name'][index].strip()
trap_string = file_name.split("_")[0] # Get the file_name string prior to the underscore
numeric_offset_beg = len("trap") # Parse the number following the 'trap' string.
numeric_offset_end = len(trap_string) - 1 # Leave off the 'c' or 'u' char.
numeric_value = trap_string[numeric_offset_beg : numeric_offset_end]
cu_value = trap_string[len(trap_string) - 1]
df['cu_int'] = int(numeric_value)
df['cu_char'] = cu_value
# The pandas dataframe is ready for number crunching.
# For now just print it out:
print df
if __name__ == "__main__":
main()
打印输出（注意发布的数据集中存在不一致 - 请参阅第1行作为示例）：
$ python read_csv.py
file_name # Date Time Temp (°C) Intensity Unnamed: 6 Unnamed: 7 Unnamed: 8 cu_int cu_char
0 trap12u_10733862_150809.txt 1 05/28/15 06:00:00.0 20.424 215.3 NaN NaN NaN 12 c
1 trap12u_10733862_150809.txt 2 05/28/15 07:00:00.0 21.091 1.0 130.2 NaN NaN 12 c
2 trap12u_10733862_150809.txt 3 05/28/15 08:00:00.0 26.195 3.0 100.0 NaN NaN 12 c
3 trap11u_10733862_150809.txt 4 05/28/15 09:00:00.0 25.222 3.0 444.5 NaN NaN 12 c
4 trap11u_10733862_150809.txt 5 05/28/15 10:00:00.0 26.195 3.0 100.0 NaN NaN 12 c
5 trap11u_10733862_150809.txt 6 05/28/15 11:00:00.0 25.902 2.0 927.8 NaN NaN 12 c
6 trap11u_10733862_150809.txt 7 05/28/15 12:00:00.0 25.708 2.0 325.0 NaN NaN 12 c
7 trap12c_10733862_150809.txt 8 05/28/15 13:00:00.0 26.292 3.0 100.0 NaN NaN 12 c
8 trap12c_10733862_150809.txt 9 05/28/15 14:00:00.0 26.390 2.0 66.7 NaN NaN 12 c
9 trap12c_10733862_150809.txt 10 05/28/15 15:00:00.0 26.097 1.0 463.9 NaN NaN 12 c