CODEWITHSUNDEEP
pythonpandasdataframe
Hidden Angle
Hidden Angle

Reputation: 59

How can I extract a specific value from a csv file using python?

I have a csv file filled with 10 years of data, and I would like to extract two specific values from the year 2018 that is contained in that large file.

    df = pd.read_csv(fn, parse_dates=[0])
    df = df.set_index('date')

This was done to extract the last trading day of each month in 2018: (only the dates came out as output, with no other data)

    start_date = '2018-01-01'
    end_date = '2018-12-31'
    months_of_2018 = pd.date_range(start_date, end_date, freq='BM')
    print(months_of_2018)

I want to extract the data of the june and september values belonging to s_001. How can I achieve that? Below is an example of how a part of my csv file looks like.

    date        s_001      s_002   
    2018-01-31  0.0031     0.0025
    2018-02-28  0.0024     0.0012
    2018-03-30  0.0021     -0.0011
    2018-04-30  -0.0010    0.0023
    2018-05-31  0.0012     0.0028
    2018-06-29  0.0015     0.0020
    2018-07-31  0.0025     0.0015
    2018-08-31  0.0017     0.0003
    2018-09-28  -0.0025    0.0009
    2018-10-31  0.0030     0.0013
    2018-11-30  0.0018     0.0005
    2018-12-31  0.0019     0.0010

Upvotes: 0

Views: 911

Answers (1)

jezrael
jezrael

Reputation: 862431

Use DatetimeIndex.month with Index.isin and DataFrame.loc for filtering by multiple months:

df = pd.read_csv(fn, index_col=[0], parse_dates=[0])


s = df.loc[df.index.month.isin([6,9]) & (df.index.year==2008), 's_001']
print (s)
date
2018-06-29    0.0015
2018-09-28   -0.0025
Name: s_001, dtype: float64

Or:

s = df.loc[df.index.strftime('%m-%Y').isin(['06-2018','09-2018']), 's_001']

Upvotes: 2

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