How to delete only containing special character rows and simultaneously retain the rest value rows?-CodePudding

Here is my code. I would like to delete the Ko_EC rows only containing the specific EC character like "--" or "3.6.3.-" and retain the rest EC character rows in a new pd.

# coding=utf-8
import pandas as pd
import numpy as np

#########
classes = [('--', 'c82241_g1', 'K07793'),
         ('3.6.3.-', 'c84674_g1', 'K10041'),
         ('1.2.5.1', 'c82377_g1', 'K00156'),
         ('3.1.1.3 2.3.1.-', 'c87035_g1', 'K14675'),
         ('2.7.2.3', 'c82661_g1', 'K00927'),
         ('1.7.99.4', 'c82688_g1', 'K00371'),
         ('1.1.1.- 1.1.1.76 1.1.1.304', 'c25949_g1', 'K03366'),
         ('1.1.1.-', 'c82777_g1', 'K18369'),
         ('4.1.1.68 5.3.3.-', 'c84443_g1', 'K05921'),
         ('--', 'c84672_g1', 'K02012'),
         ('2.2.1.1', 'c85319_g1', 'K00615'),
         ('3.1.1.-', 'c85321_g1', 'K18372'),
         ('1.8.1.2', 'c85322_g1', 'K00380'),
         ('1.2.1.16 1.2.1.79 1.2.1.20', 'c21528_g1', 'K00135'),
         ('1.10.3.-', 'c86242_g1', 'K00425')]
labels = ['Ko_EC','Gene_ID', 'Ko_id']
alls = pd.DataFrame.from_records(classes, columns=labels)

filt = (~alls['Ko_EC'].str.contains('-'))
all2 = alls.loc[filt, :]
all2

Its results:

                         Ko_EC    Gene_ID   Ko_id
2                      1.2.5.1  c82377_g1  K00156
4                      2.7.2.3  c82661_g1  K00927
5                     1.7.99.4  c82688_g1  K00371
10                     2.2.1.1  c85319_g1  K00615
12                     1.8.1.2  c85322_g1  K00380
13  1.2.1.16 1.2.1.79 1.2.1.20  c21528_g1  K00135

What I want is :

                         Ko_EC    Gene_ID   Ko_id
2                      1.2.5.1  c82377_g1  K00156
3                      3.1.1.3  c87035_g1  K14675
4                      2.7.2.3  c82661_g1  K00927
5                     1.7.99.4  c82688_g1  K00371
6           1.1.1.76 1.1.1.304  c25949_g1  K03366
8                     4.1.1.68  c84443_g1  K05921
10                     2.2.1.1  c85319_g1  K00615
12                     1.8.1.2  c85322_g1  K00380
13  1.2.1.16 1.2.1.79 1.2.1.20  c21528_g1  K00135

Here, I could retain '3', '6', and '8' rows containing the rest EC character while deleting the EC character '2.3.1.-', '1.1.1.-' '5.3.3.-', which contained special "-".

Could anyone help me? Thanks a lot.

CodePudding user response：

You can split values with remove elements if contains -, last join back and filter out rows with empty strings in boolean indexing:

alls['Ko_EC'] = [' '.join(y for y in x.split() if '-' not in y) for x in alls['Ko_EC']]

#alternative
#f = lambda x: ' '.join(y for y in x.split() if '-' not in y)
#alls['Ko_EC'] = alls['Ko_EC'].apply(f)
all2 = alls[alls['Ko_EC'].ne('')]
print (all2)
                         Ko_EC    Gene_ID   Ko_id
2                      1.2.5.1  c82377_g1  K00156
3                      3.1.1.3  c87035_g1  K14675
4                      2.7.2.3  c82661_g1  K00927
5                     1.7.99.4  c82688_g1  K00371
6           1.1.1.76 1.1.1.304  c25949_g1  K03366
8                     4.1.1.68  c84443_g1  K05921
10                     2.2.1.1  c85319_g1  K00615
12                     1.8.1.2  c85322_g1  K00380
13  1.2.1.16 1.2.1.79 1.2.1.20  c21528_g1  K00135