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

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最佳答案

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.

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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

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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)

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@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

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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)

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Try This

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

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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.

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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