python - How can I loop over only specific columns from a text file using pandas? -


i want loop:

for col in result.columns:     result[col] = result[col].str.strip("{} ")

for columns "1h.l" , "1h_2.l" because other columns aren't strings.

my code is:

import pandas pd  result = {} text = 'fe' filename = 'fe_yellow.xpk'  if text == 'ee':     df = pd.read_csv('peaks_ee.xpk', sep=" ",skiprows=5)      shift1= df["1h.p"]     shift2= df["1h_2.p"]      if filename == 'ee_pinkh1.xpk':         mask = ((shift1>5.1) & (shift1<6)) & ((shift2>7) & (shift2<8.25))     elif filename == 'ee_pinkh2.xpk':        mask = ((shift1>3.25)&(shift1<5))&((shift2>7)&(shift2<8.5))  result = df[mask] result = result[["1h.l","1h.p","1h_2.l","1h_2.p"]]  col in result.columns:     result[col] = result[col].str.strip("{} ") result.drop_duplicates(keep='first', inplace=true)  tclust_atom=open("tclust_ppm.txt","w+") result.to_string(tclust_atom, header=false)

the file reading in from:

label dataset sw sf 1h 1h_2 noesy_f1ef2e.nv 4807.69238281 4803.07373047 600.402832031 600.402832031 1h.l 1h.p 1h.w 1h.b 1h.e 1h.j 1h.u 1h_2.l 1h_2.p 1h_2.w 1h_2.b 1h_2.e 1h_2.j 1h_2.u vol int stat comment flag0 flag8 flag9 0 {1.h1'} 5.82020 0.05000 0.10000 ++ {0.0} {} {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 1 {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} {1.h1'} 5.82020 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 2 {1.h8} 8.13712 0.05000 0.10000 ++ {0.0} {} {1.h1'} 5.82020 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 3 {1.h1'} 5.82020 0.05000 0.10000 ++ {0.0} {} {1.h8} 8.13712 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 4 {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} {2.h1'} 5.90291 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 5 {2.h1'} 5.90291 0.05000 0.10000 ++ {0.0} {} {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 6 {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} {1.h1'} 5.82020 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 7 {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} {1.h8} 8.13712 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 8 {1.h1'} 5.82020 0.05000 0.10000 ++ {0.0} {} {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0 9 {1.h8} 8.13712 0.05000 0.10000 ++ {0.0} {} {2.h8} 7.61004 0.05000 0.10000 ++ {0.0} {} 0.0 100.0000 0 {} 0 0 0

i want output 

1.h1' 5.82020 0.3 2.h8 7.61004 0.3 1.h8 8.13712 0.3 2.h1' 5.90291 0.3

the first column comes columns "1h.l" , "1h_2.l" second "1h.p" , "1h_2.p" , third column want want write every row. how can this?

you can pass list of columns names i.e 

result = pd.dataframe({"1h.l":['{nice}','{so}'],"1h_2.l":['{nice}','{so}'],"2h.l":['nice','so']})  col in ['1h.l','1h_2.l']:     result[col] = result[col].str.strip("{} ")

output : 

    1h.l 1h_2.l  2h.l 0  nice   nice  nice 1

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