How do I add columns to a data frame?
I have the following data:
Example:
DRIVER_ID; TSHEZTAMR; POSITION
156; 2014-02-01 00: 00: 00.739166 + 01; POINT (41.8836718276551 12.4877775603346)
I want to create a pandas framework with 4 columns that are id, time, longitude, latitude. So far I got:
cur_cab = pd.DataFrame.from_csv(
path,
sep=";",
header=None,
parse_dates=[1]).reset_index()
cur_cab.columns = ['cab_id', 'datetime', 'point']
path
specifies a .txt file containing data. I already wrote a function that returns longitude and latitude values from a gated point.
How to expand dataframe with extra column and split values?
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Once downloaded, if you are using the latest version of pandas, you can use vectorized methods str
to parse the column:
In [87]:
df['pos_x'], df['pos_y']= df['point'].str[6:-1].str.split(expand=True)
df
Out[87]:
cab_id datetime \
0 156 2014-01-31 23:00:00.739166
point pos_x pos_y
0 POINT(41.8836718276551 12.4877775603346) 0 1
Also you have to stop using it from_csv
, it doesn't update anymore, use the top level read_csv
so your download code is:
cur_cab = pd.read_csv(
path,
sep=";",
header=None,
parse_dates=[1],
names=['cab_id', 'datetime', 'point'],
skiprows=1)
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