Importing Excel into Panda Dataframe

Question

The following is only the beginning for an Coursera assignment on Data Science. I hope this is not to trivial for. But I am lost on this and could not find an answer. I am a

Answer 1

I modified your code and was able to get the data into the dataframe. Instead of skipcolumns (which did not work), I used the argument usecols as follows

energy=pd.read_excel('Energy_Indicators.xls',
                     sheetname='Energy',
                     header=16,
                     skiprows=[16],
                     skipfooter=38,
                     usecols=[2,3,4,5]
                    )

    Unnamed: 2      Petajoules  Gigajoules  %
0   Afghanistan     321         10          78.669280
1   Albania         102         35          100.000000
2   Algeria         1959        51          0.551010
3   American Samoa  ...         ...         0.641026
4   Andorra         9           121         88.695650

In order to make the countries as the index, you can do the following

# Rename the column Unnamed: 2 to Country
energy = energy.rename(columns={'Unnamed: 2':'Country'})

# Change the index to country column    
energy.index = energy['Country']

# Drop the extra country column
energy = energy.drop('Country', axis=1)

Answer 2

I installed xlrd package, with pip install xlrd and then loaded the file successfully as follows:

In [17]: df = pd.read_excel(r"http://unstats.un.org/unsd/environment/excel_file_tables/2013/Energy%20Indicators.xls",
    ...:                      sheetname='Energy',
    ...:                      header=16,
    ...:                      skiprows=[17],
    ...:                      skipfooter=38,
    ...:                      skipcolumns=2)  

In [18]: df.shape 
Out[18]: (227, 3)

In [19]: df.head() 
Out[19]: 
                                  Energy Supply Energy Supply per capita  \
NaN Afghanistan    Afghanistan              321                       10   
    Albania        Albania                  102                       35   
    Algeria        Algeria                 1959                       51   
    American Samoa American Samoa           ...                      ...   
    Andorra        Andorra                    9                      121   

                                   Renewable Electricity Production  
NaN Afghanistan    Afghanistan                            78.669280  
    Albania        Albania                               100.000000  
    Algeria        Algeria                                 0.551010  
    American Samoa American Samoa                          0.641026  
    Andorra        Andorra                                88.695650  

In [20]: pd.__version__ 
Out[20]: u'0.20.3'

In [21]: df.columns 
Out[21]: 
Index([u'Energy Supply', u'Energy Supply per capita',
       u'Renewable Electricity Production'],
      dtype='object')

Notice that I am using the last version of pandas 0.20.3 make sure you have the latest version on your system.

Answer 3

I think you need add parameters:

• index_col for convert column to index
• usecols - parse columns by positions
• change header position to 15

---

energy=pd.read_excel('Energy Indicators.xls',
                     sheetname='Energy',
                     skiprows=[17],
                     skipfooter=38,
                     header=15,
                     index_col=[0],
                     usecols=[2,3,4,5]
                    )
print (energy.head())

               Energy Supply Energy Supply per capita  \
Afghanistan              321                       10   
Albania                  102                       35   
Algeria                 1959                       51   
American Samoa           ...                      ...   
Andorra                    9                      121   

                Renewable Electricity Production  
Afghanistan                            78.669280  
Albania                               100.000000  
Algeria                                 0.551010  
American Samoa                          0.641026  
Andorra                                88.695650