Making subsets of DataFrame

Question

To build an algorithm I want to make python script to work in such a way that it doesn't needs to make use of Panda's read_csv function again and again.

Following is the code that I am using.

start_date = '2016-06-01'
end_date = '2017-09-22'

#Pool of symbols that I want to use
usesymbols = ['GLAXO', 'AVN']

#Function to build a dataframe 
def data(symbols):
    dates=pd.date_range(start_date,end_date) 
    df=pd.DataFrame(index=dates)
    for symbol in symbols:
        df_temp=pd.read_csv('/home/furqan/Desktop/python_data/{}.csv'.format(str(symbol)),usecols=['Date','Close'],
                            parse_dates=True,index_col='Date',na_values=['nan'])
        df_temp = df_temp.rename(columns={'Close': symbol})
        df=df.join(df_temp)
        df=df.fillna(method='ffill')
        df=df.fillna(method='bfill')
    return df

#Function to build powerset from list of "usesymbols"
def powerset(iterable):
    s = list(iterable)
    return chain.from_iterable(combinations(s, r) for r in range(1, len(s)+1))

power_set = list(powerset(usesymbols))
dataframe = data(usesymbols)
print(dataframe)
for j in range(0, len(power_set)):

Using usesymbols first I gernerated a power set which looks like as follows:

[('GLAXO',), ('AVN',), ('GLAXO', 'AVN')]

then I created a dataframe which looks like as follows:

             GLAXO    AVN
2016-06-01  205.93  31.42
2016-06-02  206.22  32.62
2016-06-03  207.86  31.65
2016-06-04  207.86  31.65
2016-06-05  207.86  31.65

After that I added a loop, under that loop I want to create a temporary dataframe such that if j = 0 that temporary dataframe should consist of 1 column namely GLAXO, then when j = 1 it should consist of one column 'AVN' and finally when j = 3 it should comprise of both the columns 'AVN' and 'GLAXO'.

I am having difficulty in making that temporary dataframe. Second option is to make use of data function, but that would end up using pandas read_csv function every time.

chrisckwong821 · Accepted Answer · 2017-09-25 05:26:05Z

1

powerset = [('GLAXO'), ('AVN'), ('GLAXO', 'AVN')]
j = 1
print(df.loc[:,powerset[j]])

2016-06-01    31.42
2016-06-02    32.62
2016-06-03    31.65
2016-06-04    31.65
2016-06-05    31.65
Name: AVN, dtype: float64

j=2
print(df.loc[:,powerset[j]])

 GLAXO    AVN
2016-06-01  205.93  31.42
2016-06-02  206.22  32.62
2016-06-03  207.86  31.65
2016-06-04  207.86  31.65
2016-06-05  207.86  31.65

answered Sep 25, 2017 at 5:26

chrisckwong821

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1 Comment

Furqan Hashim Over a year ago

Perfect solution.

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