CODEWITHSUNDEEP
pythonpandas
curiousguy
curiousguy

Reputation: 3262

pandas dataframe change column value

I have python dict like this:

keysdict={'date': {20: '201012', 21: '201101', 22: '201102', 23: '201103', 24: '201104', 25: '201105', 26: '201106', 27: '201107', 28: '201108', 29: '201109', 30: '201110', 31: '201111'}}

And I have pandas dataframe like this 

A    B
20  0.123
21  2.123
22  4.45
23  3.2
24  3.1
25  3.9
26  4.2

Now I want to add an extra column C which takes the respective value from dict keys that are in Column A . Like below one 

A    B      C
20  0.123  201012 
21  2.123  201101
22  4.45   201102
23  3.2    201103
24  3.1    201104
25  3.9    201105
26  4.2    201106

I tried this 

df.loc[:,'C']=keysdict['date'][df.loc['A']]

But getting below error

KeyError: 'the label [A] is not in the [index]

Upvotes: 0

Views: 179

Answers (3)

Vaishali
Vaishali

Reputation: 38415

You can directly use map without apply

df['C'] = df['A'].map(keysdict['date'])

    A   B       C
0   20  0.123   201012
1   21  2.123   201101
2   22  4.450   201102
3   23  3.200   201103
4   24  3.100   201104
5   25  3.900   201105
6   26  4.200   201106

Upvotes: 3

A.Kot
A.Kot

Reputation: 7903

Try map instead:

df['C'] = df['A'].map(keysdict['date'])

If column 'A' is an index:

df['C'] = df.map(keysdict['date'])

Upvotes: 3

DYZ
DYZ

Reputation: 57033

df.loc['A'] refers to the row labeled 'A', and you need column, which is accessed as df['A']. Here's the correct code:

df = pd.DataFrame({'A':[20,21,22,23], 'B':[0.123,2.123,4.45,3.2]})
#    A      B
#0  20  0.123
#1  21  2.123
#2  22  4.450
#3  23  3.200

Sample key dictionary:

keysdict = {'date' : {20:0,21:1,22:2,23:3}}

df['C'] = df['A'].apply(lambda x: keysdict['date'][x])
#    A      B  C
#0  20  0.123  0
#1  21  2.123  1
#2  22  4.450  2
#3  23  3.200  3

Upvotes: 1

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