Python Pandas Dataframe - remove data from dataframe if indexed date is older than a certain date

Question

I have a dataframe (df) which is indexed by date

date             BBG.XSWX.KABN.S  BBG.XETR.TKA.S                        
2014-02-03       328.657522          19.083
2014-02-04       327.776510          18.809
2014-02-05       325.657202          18.337
2014-02-06       330.845170          18.690
2014-02-07       334.789668          19.153

Is there a way to remove any rows that have an indexed date which is older than say 2014-02-06, so I would have the resulting dataframe:

date             BBG.XSWX.KABN.S  BBG.XETR.TKA.S                       
2014-02-06       330.845170          18.690
2014-02-07       334.789668          19.153

the edits made by @users4393829 don't correct what is perfectly correct code by the OP i.e. the index (here 'date') can correctly be one level down! — Vidhya G
– Vidhya G, Commented Jun 30, 2015 at 7:53

sachin saxena · Accepted Answer · 2015-06-30 06:59:54Z

5

you might want to try :

df.loc[df.index < '2014-02-06']

if your index is in datetime format then

df.loc[df.index < pd.to_datetime('2014-02-06')]

answered Jun 30, 2015 at 6:59

sachin saxena

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Comments

Vidhya G · Accepted Answer · 2015-06-30 17:25:18Z

1

Pandas does allow row slicing:

>>> df['2014-02-06':]
            BBG.XSWX.KABN.S  BBG.XETR.TKA.S
date                                       
2014-02-06       330.845170          18.690
2014-02-07       334.789668          19.153

answered Jun 30, 2015 at 17:25

Vidhya G

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