Replace() does not find dates and does not convert to another string

Question

I have an array in csv:

    date        group
0   2015-01-02  WODKA
1   2015-01-02  PIWO
2   2015-01-02  2015-01-02
3   2015-01-03  WODKA
4   2015-01-03  PIWO
5   2015-01-03  2015-01-03
6   2015-01-03  WODKA
7   2015-01-03  PIWO

And I would like to convert all the dates from the column "group" to the word "sum". But my code does not work...

import pandas as pd
import numpy as np
from datetime import datetime as dt

x = pd.read_csv("C:\\Users\dell\\Desktop\\list_1.csv", sep=';')
x.group = x.group.replace(dt, 'sum')

Why do you think that would work? dt is a module object, do you have a bunch of references to the dt module -object in your group column? — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Oct 25, 2017 at 20:54

MaxU - stand with Ukraine · Accepted Answer · 2017-10-25 20:55:15Z

5

we can update those rows where we could convert group to datetime:

In [40]: df.loc[pd.to_datetime(df['group'], errors='coerce').notnull(), 'group'] = 'sum'

In [41]: df
Out[41]:
         date  group
0  2015-01-02  WODKA
1  2015-01-02   PIWO
2  2015-01-02    sum
3  2015-01-03  WODKA
4  2015-01-03   PIWO
5  2015-01-03    sum
6  2015-01-03  WODKA
7  2015-01-03   PIWO

or using RegEx (NOTE: first solution is much more flexible as it'll support different date formats):

In [46]: df['sum'] = df['group'].str.replace(r'^\d{4}-\d{2}-\d{2}', 'sum')

In [47]: df
Out[47]:
         date       group    sum
0  2015-01-02       WODKA  WODKA
1  2015-01-02        PIWO   PIWO
2  2015-01-02  2015-01-02    sum
3  2015-01-03       WODKA  WODKA
4  2015-01-03        PIWO   PIWO
5  2015-01-03  2015-01-03    sum
6  2015-01-03       WODKA  WODKA
7  2015-01-03        PIWO   PIWO

answered Oct 25, 2017 at 20:55

MaxU - stand with Ukraine

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9 Comments

Tomasz Przemski Over a year ago

Works great, that was it! There are still many lessons ahead of me :) Thanks!

MaxU - stand with Ukraine Over a year ago

@TomaszPrzemski, glad i could help :)

BENY Over a year ago

@TomaszPrzemski I will suggested you accept MaxU's answer instead of mine ,since it is well documented by pandas API , if you like my answer you can upvote . We need to consider the future visitors and bring them to the 100% right answer.

MaxU - stand with Ukraine Over a year ago

@Wen, thank you! I think it's up to OP to chose the best answer. :) PS you have my upvote already...

Tomasz Przemski Over a year ago

@MaxU Only justice, because in my project I used your solution :)

|

BENY · Accepted Answer · 2017-10-25 22:25:40Z

4

Or do some trick with special mark -( Notice , I will recommend MaxU's answer)

df.group.replace({'-':np.nan},regex=True).fillna('sum')
Out[449]: 
0    WODKA
1     PIWO
2      sum
3    WODKA
4     PIWO
5      sum
6    WODKA
7     PIWO
Name: group, dtype: object

edited Oct 25, 2017 at 22:25

answered Oct 25, 2017 at 20:58

BENY

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8 Comments

roganjosh Over a year ago

This reminds me of our last discussion that prompted a question in itself :). Where are you learning these tricks, I've not seen anything like them when I'm searching for my own problems?

roganjosh Over a year ago

Source code, not docs, then? Do they explicitly state as comments in the source code that such approaches will give the desired results, or do you identify these approaches yourself from understanding the code?

BENY Over a year ago

@roganjosh github.com/pandas-dev/pandas/blob/v0.20.3/pandas/core/…

BENY Over a year ago

@roganjosh Man , if you know me more, you will find I never ever fight for any point(reputation) related thing in SO. :-)

BENY Over a year ago

@roganjosh I am asking it as an question :-) stackoverflow.com/questions/46944650/…

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