I have a pandas dataframe with a column as datatime that looks like:
data.ts_placed
Out[68]:
1 2008-02-22 15:30:40
2 2008-03-20 16:56:00
3 2008-06-14 21:26:02
4 2008-06-16 10:26:02
5 2008-06-23 20:41:03
6 2008-07-17 08:02:00
7 2008-10-13 12:47:05
8 2008-11-14 09:20:33
9 2009-02-23 11:24:18
10 2009-03-02 10:29:19
I'd like to slice the dataframe by eliminating all rows before 2009
To slice the columns, the syntax is df. loc[:,start:stop:step] ; where start is the name of the first column to take, stop is the name of the last column to take, and step as the number of indices to advance after each extraction; for example, you can select alternate columns.
Slicing a DataFrame in Pandas includes the following steps:Ensure Python is installed (or install ActivePython) Import a dataset. Create a DataFrame. Slice the DataFrame.
You can use a simple string comparison to compare the values against a year string:
In [63]:
df.loc[df['date'] >= '2009']
Out[63]:
date
index
9 2009-02-23 11:24:18
10 2009-03-02 10:29:19
Or use the dt
attribute to access the year:
In [64]:
df.loc[df['date'].dt.year >= 2009]
Out[64]:
date
index
9 2009-02-23 11:24:18
10 2009-03-02 10:29:19
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