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efueyo
Asked: 2020-06-24 07:51:04 +0800 CST 2020-06-24 07:51:04 +0800 CST

transform data frame

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I have the dataframe

            Acatis  TrueValue  ValorRelativo
Date                                        
2015-12-29  220.43     12.959         12.311
2020-05-13  270.27     12.870         13.234

I need to transform it into this other one.

          Nombre        Date    Close
0         Acatis  2015-12-29  220.430
1         Acatis  2020-05-13  270.270
2      TrueValue  2015-12-29   12.959
3      TrueValue  2020-05-13   12.870
4  ValorRelativo  2015-12-29   12.311
5  ValorRelativo  2020-05-13   13.234

Is it possible to do it by applying some method/s?

Indeed, using "melt" it can be done like this:

p1 = pd.melt(df_analisis, id_vars =['Date'], value_vars =['Acatis']) 
p2 = pd.melt(df_analisis, id_vars =['Date'], value_vars =['TrueValue']) 
p3 = pd.melt(df_analisis, id_vars =['Date'], value_vars =['ValorRelativo']) 

datos  = pd.concat([p1, p2, p3], join="inner")
datos

The output is:

        Date       variable    value
0 2015-12-29         Acatis  220.430
1 2020-05-13         Acatis  270.270
0 2015-12-29      TrueValue   12.959
1 2020-05-13      TrueValue   12.870
0 2015-12-29  ValorRelativo   12.311
1 2020-05-13  ValorRelativo   13.234

Is there a more direct way?

python-3.x

1 Answers

  1. Best Answer

    I think what you are looking for is a function called melt, which is present in the Pandas library.

    Here is the link to the documentation:

    [1] https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.melt.html

    The solution would be something like this:

    pd.melt(df_analisis, id_vars =['Date'], value_vars =['Acatis', 'TrueValue', 'ValorRelativo'])
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