pandas dataframe data sorting

Question

I have a dataset which looks like following-

|      year     |     state   |district| Party|
|---------------|-------------|--------|------|
|          2010 |     haryana |kaithal | INC|
|          2010 |     haryana |kaithal | bjp|
|          2010 |     haryana |kaithal |NOTA|
|          2010 |     goa     |panji   | AAP|
|          2010 |     goa     |panji   | INC|
|          2010 |     goa     |panji   | BJP|
|          2013 |     up      |meerut  | INC|
|          2013 |     up      |meerut  | SP |
|          2015 |     haryana |kaithal |INC |
|          2015 |     haryana |kaithal |BJP |
|          2015 |     haryana |kaithal |AAP |

I want to rename INC to major for year 2010 and BJP to major in 2015. I need data in the following manner-

year	state	district	Party
2010	haryana	kaithal	major
2010	haryana	kaithal	bjp
2010	haryana	kaithal	NOTA
2010	goa	panji	AAP
2010	goa	panji	major
2010	goa	panji	BJP
2013	up	meerut	major
2013	up	meerut	SP
2015	haryana	kaithal	INC
2015	haryana	kaithal	major
2015	haryana	kaithal	AAP

I am using the code-

for state in df['state']:
  if state=='haryana':
    for year in df['year']:
      if year==2010:
        df['party'].replace('INC','major',inplace=True)
      else:
         continue
      if year==2015:
        df['party'].replace('BJP','major',inplace=True)
  else:
    continue

But this code is taking a lot of time to run and not giving the desired results as it is just considering replacing INC to major in all years and does not replace BJP.

because also replacement if df.state=='goa' or df.state=='up' — jezrael
– jezrael, Commented Dec 6, 2022 at 11:38
What is your complete code? if state=='haryana': is wrong there in question? — jezrael
– jezrael, Commented Dec 6, 2022 at 11:52
the code i have written is not working. It was just a sample for one state, to know if there is some mistake there. I am trying your solution, it is not giving the required results. I am using m1=(df['STATE']=='BIHAR') & (df['YEAR']==2010) & ((df['PARTY']=='BJP')|(df['PARTY']=='JD(U)')) m2=(df['STATE']=='BIHAR') & (df['YEAR']==2015) & ((df['PARTY']=='RJD')|(df['PARTY']=='JD(U)')) m3=(df['STATE']=='BIHAR') & (df['YEAR']==2020) & ((df['PARTY']=='BJP')|(df['PARTY']=='JD(U)')) m=m1|m2|m3 df.loc[m, 'PARTY']= 'MAJOR' this is making all three parties major in all three years. — NoobCoderPy
– NoobCoderPy, Commented Dec 6, 2022 at 11:57
One idea, if check print (df[df['PARTY']=='JD(U)')]) return correct rows? — jezrael
– jezrael, Commented Dec 6, 2022 at 12:01

Timeless · Accepted Answer · 2022-12-06 11:30:18Z

2

You can use boolean indexing with pandas.DataFrame.loc :

m1= (df["year"].eq(2010)) & (df["Party"].eq("INC"))
m2= (df["year"].eq(2015)) & (df["Party"].eq("BJP"))

df.loc[m1|m2, "Party"] = "major"

# Ouptut :

  print(df.to_string())
    year    state district  Party
0   2010  haryana  kaithal  major
1   2010  haryana  kaithal    bjp
2   2010  haryana  kaithal   NOTA
3   2010      goa    panji    AAP
4   2010      goa    panji  major
5   2010      goa    panji    BJP
6   2013       up   meerut    INC
7   2013       up   meerut     SP
8   2015  haryana  kaithal    INC
9   2015  haryana  kaithal  major
10  2015  haryana  kaithal    AAP

answered Dec 6, 2022 at 11:30

Timeless

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Comments

jezrael · Accepted Answer · 2022-12-06 12:10:36Z

1

Chain 3 conditions for compare each 3 values and set new values in DataFrame.loc:

m1 = (df.state=='haryana') & (df['year'] == 2010) & (df['party'] == 'INC')
m2 = (df.state=='haryana') & (df['year'] == 2015) & (df['party'] == 'BJP')
m = m1 | m2

Or:

m = (df.state=='haryana') & ((df['year'] == 2010) & (df['party'] == 'INC') |
                             (df['year'] == 2015) & (df['party'] == 'BJP'))

df.loc[m, 'party'] = 'major'

EDIT: You can check ouput of masks if working well:

m1=(df['STATE']=='BIHAR') & (df['YEAR']==2010) & ((df['PARTY']=='BJP')|(df['PARTY']=='JD(U)')) 
m2=(df['STATE']=='BIHAR') & (df['YEAR']==2015) & ((df['PARTY']=='RJD')|(df['PARTY']=='JD(U)')) 
m3=(df['STATE']=='BIHAR') & (df['YEAR']==2020) & ((df['PARTY']=='BJP')|(df['PARTY']=='JD(U)')) m=m1|m2|m3 df.loc[m, 'PARTY']= 'MAJOR'

print (df.assign(m1=m1, m2=m2, m3=m3,triple= m1 | m2 | m3,
                BIHAR = (df['STATE']=='BIHAR'),
                Y2010 = (df['YEAR']==2010)))

edited Dec 6, 2022 at 12:10

answered Dec 6, 2022 at 11:31

jezrael

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2 Comments

Timeless Over a year ago

In the expected output shared by the OP, where state=="goa", INC got replaced by major.

jezrael Over a year ago

@abokey - ggod point, I ask OP in comments

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