@@ -971,6 +971,57 @@ Parsing date components in multi-columns is faster with a format
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In [36 ]: % timeit pd.to_datetime(ds)
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1 loops, best of 3 : 488 ms per loop
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+ Skip row between header and data
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+ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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+
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+ .. ipython :: python
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+
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+ from io import StringIO
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+ import pandas as pd
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+
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+ data = """ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ ;;;;
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+ date;Param1;Param2;Param4;Param5
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+ ;m²;°C;m²;m
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+ ;;;;
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+ 01.01.1990 00:00;1;1;2;3
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+ 01.01.1990 01:00;5;3;4;5
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+ 01.01.1990 02:00;9;5;6;7
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+ 01.01.1990 03:00;13;7;8;9
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+ 01.01.1990 04:00;17;9;10;11
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+ 01.01.1990 05:00;21;11;12;13
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+ """
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+
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+ Option 1: pass rows explicitly to skiprows
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+ """"""""""""""""""""""""""""""""""""""""""
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+
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+ .. ipython :: python
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+
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+ pd.read_csv(StringIO(data.decode(' UTF-8' )), sep = ' ;' , skiprows = [11 ,12 ],
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+ index_col = 0 , parse_dates = True , header = 10 )
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+
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+ Option 2: read column names and then data
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+ """""""""""""""""""""""""""""""""""""""""
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+
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+ .. ipython :: python
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+
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+ pd.read_csv(StringIO(data.decode(' UTF-8' )), sep = ' ;' ,
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+ header = 10 , parse_dates = True , nrows = 10 ).columns
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+ columns = pd.read_csv(StringIO(data.decode(' UTF-8' )), sep = ' ;' ,
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+ header = 10 , parse_dates = True , nrows = 10 ).columns
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+ pd.read_csv(StringIO(data.decode(' UTF-8' )), sep = ' ;' ,
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+ header = 12 , parse_dates = True , names = columns)
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+
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+
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+
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.. _cookbook.sql :
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SQL
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