Slicing Data Frame through its Index and array in python

Alex_MN Published at Dev

Alex_MN

I have a sample dataframe df and an array n as shown below. I want to filter based on the array values which are in index. The output dataframe is shown below as well. I have tried Out = df[df.index == n] , Out = df.loc[df.index == n] and df.loc[n] which is not working giving an error Lengths must match to compare. Can anyone help me in solving this. Here the array is the row number corresponding to data frame.

df = 
             Open   High    Low    Close    Adj Close   Volume
2007-06-18  0.33979 0.33979 0.33979 0.33979 0.33979 1591888
2007-06-29  0.33074 0.33074 0.33074 0.33074 0.33074 88440
2007-06-20  0.33526 0.33526 0.33526 0.33526 0.33526 3538
2007-06-21  0.32113 0.32113 0.32113 0.32113 0.32113 3550
2007-06-22  0.34713 0.34713 0.34713 0.34713 0.34713 670
2007-06-16  0.33979 0.33979 0.33979 0.33979 0.33979 1591888
2007-06-30  0.33074 0.33074 0.33074 0.33074 0.33074 88440
2007-06-31  0.33526 0.33526 0.33526 0.33526 0.33526 3538
2007-06-44  0.32113 0.32113 0.32113 0.32113 0.32113 3550
2007-06-22  0.34713 0.34713 0.34713 0.34713 0.34713 670

n = array([0, 1, 2, 3])

Out  = 
            Open      High  Low     Close   Adj Close   Volume
2007-06-18  0.33979 0.33979 0.33979 0.33979 0.33979 1591888
2007-06-29  0.33074 0.33074 0.33074 0.33074 0.33074 88440
2007-06-20  0.33526 0.33526 0.33526 0.33526 0.33526 3538
2007-06-21  0.32113 0.32113 0.32113 0.32113 0.32113 3550

jezrael

Use DataFrame.iloc for select by positions:

n = np.array([     0,      1,      2, 3])
df = df.iloc[n]
print (df)
               Open     High      Low    Close  Adj Close   Volume
2007-06-18  0.33979  0.33979  0.33979  0.33979    0.33979  1591888
2007-06-29  0.33074  0.33074  0.33074  0.33074    0.33074    88440
2007-06-20  0.33526  0.33526  0.33526  0.33526    0.33526     3538
2007-06-21  0.32113  0.32113  0.32113  0.32113    0.32113     3550

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edited at2020-11-30

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