pandas dataframe- replace row values

Question

I have a dataframe with four columns (see input dataframe below). I need to check if Meta column has pattern relation (example M_relation) then add number from relation column to the meta column value. How this can be done in pandas?

Input dataframe:

--------------------------------------

    Entry1 | Relation | Entry2 | Meta |

--------------------------------------

E11 | R_31 | E21 | M_xxx |

E12 | R_21 | E51 | M_relation |

E33 | R_21 | E51 | M_yyy |

E44 | R_41 | E46 | M_relation |

Output:

--------------------------------------
Entry1 | Relation | Entry2 | Meta |
--------------------------------------

E11 | R_31 | E21 | M_xxx |

E12 | R_21 | E51 | M_relation_21 |

E33 | R_21 | E51 | M_yyy |

E44 | R_41 | E46 | M_relation_41 |
--------------------------------------

Can you show what you have tried?

Merlin
– Merlin

2016-06-21 01:15:28 +00:00
Commented Jun 21, 2016 at 1:15 — Merlin
– Merlin, Commented Jun 21, 2016 at 1:15

Stefan · Accepted Answer · 2016-06-21 00:37:43Z

1

You could:

pattern = df.Meta.str.split('_').str.get(1) == 'relation'
df.loc[pattern, 'Meta'] = df.loc[pattern, 'Meta'] + '_' + df.loc[pattern, 'Relation'].str.split('_').str.get(1)

to get:

  Entry1 Relation Entry2           Meta
0    E11     R_31    E21          M_xxx
1    E12     R_21    E51  M_relation_21
2    E33     R_21    E51          M_yyy
3    E44     R_51    E51  M_relation_51

edited Jun 21, 2016 at 0:37

answered Jun 21, 2016 at 0:20

Stefan

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