CODEWITHSUNDEEP
pythonpandasdata-analysis
user517696
user517696

Reputation: 2672

How do I change a single index value in pandas dataframe?

energy.loc['Republic of Korea']

I want to change the value of index from 'Republic of Korea' to 'South Korea'. But the dataframe is too large and it is not possible to change every index value. How do I change only this single value?

Upvotes: 103

Views: 196351

Answers (8)

mirekphd
mirekphd

Reputation: 6743

And if your DataFrame has RangeIndex (see docs), like this single-row df:

>>> df.index
RangeIndex(start=0, stop=1, step=1)

>>> df.index.values
array([0])

... you can change the index value(s) with:

new_index=42
df.index = pd.RangeIndex(start=new_index, stop=new_index+1, step=1)

... to obtain the desired effect:

>>> df.index
RangeIndex(start=42, stop=43, step=1)

>>> df.index.values
array([42])

Upvotes: 0

bhargav3vedi
bhargav3vedi

Reputation: 619

We can use rename function to change row index or column name. Here is the example,

Suppose data frame is like given below,

       student_id     marks
index
  1        12          33
  2        23          98
  • To change index 1 to 5

we will use axis = 0 which is for row

df.rename({ 1 : 5 }, axis=0)

df refers to data frame variable. So, output will be like

       student_id     marks
index
  5        12          33
  2        23          98
  • To change column name

we will have to use axis = 1

df.rename({ "marks" : "student_marks" }, axis=1)

so, changed data frame is

       student_id     student_marks
index
  5        12              33
  2        23              98

Upvotes: 2

mpeli
mpeli

Reputation: 367

This seems to work too:

energy.index.values[energy.index.tolist().index('Republic of Korea')] = 'South Korea'

No idea though whether this is recommended or discouraged.

Upvotes: 1

S.V
S.V

Reputation: 2793

If you have MultiIndex DataFrame, do this:

# input DataFrame
import pandas as pd
t = pd.DataFrame(data={'i1':[0,0,0,0,1,1,1,1,2,2,2,2],
                       'i2':[0,1,2,3,0,1,2,3,0,1,2,3],
                       'x':[1.,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.]})
t.set_index(['i1','i2'], inplace=True)
t.sort_index(inplace=True)

# changes index level 'i1' values 0 to -1
t.rename(index={0:-1}, level='i1', inplace=True)

Upvotes: 13

ErnestScribbler
ErnestScribbler

Reputation: 2967

@EdChum's solution looks good. Here's one using rename, which would replace all these values in the index.

energy.rename(index={'Republic of Korea':'South Korea'},inplace=True)

Here's an example

>>> example = pd.DataFrame({'key1' : ['a','a','a','b','a','b'],
           'data1' : [1,2,2,3,nan,4],
           'data2' : list('abcdef')})
>>> example.set_index('key1',inplace=True)
>>> example
      data1 data2
key1             
a       1.0     a
a       2.0     b
a       2.0     c
b       3.0     d
a       NaN     e
b       4.0     f

>>> example.rename(index={'a':'c'}) # can also use inplace=True
      data1 data2
key1             
c       1.0     a
c       2.0     b
c       2.0     c
b       3.0     d
c       NaN     e
b       4.0     f

Upvotes: 131

Andrea C
Andrea C

Reputation: 329

Here's another good one, using replace on the column.

df.reset_index(inplace=True)
df.drop('index', axis = 1, inplace=True)
df["Country"].replace("Republic of Korea", value="South Korea", inplace=True)
df.set_index("Country", inplace=True)

Upvotes: 9

Andrea C
Andrea C

Reputation: 329

Here's another idea based on set_value

df = df.reset_index()
df.drop('index', axis = 1, inplace=True)
index = df.index[df["Country"] == "Republic of Korea"]
df.set_value(index, "Country", "South Korea")
df = df.set_index("Country")
df["Country"] = df.index

Upvotes: 5

Batman
Batman

Reputation: 8917

You want to do something like this:

as_list = df.index.tolist()
idx = as_list.index('Republic of Korea')
as_list[idx] = 'South Korea'
df.index = as_list

Basically, you get the index as a list, change that one element, and the replace the existing index.

Upvotes: 85

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