11  Localiza columnas y renglones

En está sesión , nos enfocaremos en técnicas que van desde la selección de columnas hasta la manipulación de filas con .loc y .iloc, herramientas que te empoderarán para manejar tus datos temporales en Pandas con eficacia.

Acceder a las columnas, ya sea utilizando corchetes, la notación de punto te cambiará tu flujo de trabajo. Estas estrategias no solo facilitan la selección de datos relevantes sino que también optimizan el proceso de análisis temporal.

import pandas as pd
f = "../data/Cuernavaca_1dia_comas.csv"
cuerna = pd.read_csv(f,index_col=0,parse_dates=True)
cuerna.head()
To Ws Wd P Ig Ib Id
tiempo
2012-01-01 00:00:00 19.3 0.0 26 87415 0 0 0
2012-01-01 01:00:00 18.6 0.0 26 87602 0 0 0
2012-01-01 02:00:00 17.9 0.0 30 87788 0 0 0
2012-01-01 03:00:00 17.3 0.0 30 87554 0 0 0
2012-01-01 04:00:00 16.6 0.0 27 87321 0 0 0 
cuerna['To']
tiempo
2012-01-01 00:00:00    19.3
2012-01-01 01:00:00    18.6
2012-01-01 02:00:00    17.9
2012-01-01 03:00:00    17.3
2012-01-01 04:00:00    16.6
2012-01-01 05:00:00    15.9
2012-01-01 06:00:00    17.0
2012-01-01 07:00:00    18.0
2012-01-01 08:00:00    19.0
2012-01-01 09:00:00    20.0
2012-01-01 10:00:00    20.0
2012-01-01 11:00:00    20.0
2012-01-01 12:00:00    21.0
2012-01-01 13:00:00    22.0
2012-01-01 14:00:00    21.7
2012-01-01 15:00:00    21.3
2012-01-01 16:00:00    21.0
2012-01-01 17:00:00    19.0
2012-01-01 18:00:00    17.1
2012-01-01 19:00:00    17.0
2012-01-01 20:00:00    17.3
2012-01-01 21:00:00    17.0
2012-01-01 22:00:00    16.6
2012-01-01 23:00:00    15.9
Name: To, dtype: float64
cuerna.To #Por esto no conviene usar espacios o caracteres extraños
tiempo
2012-01-01 00:00:00    19.3
2012-01-01 01:00:00    18.6
2012-01-01 02:00:00    17.9
2012-01-01 03:00:00    17.3
2012-01-01 04:00:00    16.6
2012-01-01 05:00:00    15.9
2012-01-01 06:00:00    17.0
2012-01-01 07:00:00    18.0
2012-01-01 08:00:00    19.0
2012-01-01 09:00:00    20.0
2012-01-01 10:00:00    20.0
2012-01-01 11:00:00    20.0
2012-01-01 12:00:00    21.0
2012-01-01 13:00:00    22.0
2012-01-01 14:00:00    21.7
2012-01-01 15:00:00    21.3
2012-01-01 16:00:00    21.0
2012-01-01 17:00:00    19.0
2012-01-01 18:00:00    17.1
2012-01-01 19:00:00    17.0
2012-01-01 20:00:00    17.3
2012-01-01 21:00:00    17.0
2012-01-01 22:00:00    16.6
2012-01-01 23:00:00    15.9
Name: To, dtype: float64
cuerna[["Ws","To"]]
Ws To
tiempo
2012-01-01 00:00:00 0.0 19.3
2012-01-01 01:00:00 0.0 18.6
2012-01-01 02:00:00 0.0 17.9
2012-01-01 03:00:00 0.0 17.3
2012-01-01 04:00:00 0.0 16.6
2012-01-01 05:00:00 0.0 15.9
2012-01-01 06:00:00 0.0 17.0
2012-01-01 07:00:00 0.0 18.0
2012-01-01 08:00:00 0.0 19.0
2012-01-01 09:00:00 0.0 20.0
2012-01-01 10:00:00 1.0 20.0
2012-01-01 11:00:00 2.1 20.0
2012-01-01 12:00:00 1.8 21.0
2012-01-01 13:00:00 1.5 22.0
2012-01-01 14:00:00 1.3 21.7
2012-01-01 15:00:00 1.2 21.3
2012-01-01 16:00:00 1.0 21.0
2012-01-01 17:00:00 0.0 19.0
2012-01-01 18:00:00 0.0 17.1
2012-01-01 19:00:00 0.0 17.0
2012-01-01 20:00:00 0.0 17.3
2012-01-01 21:00:00 0.2 17.0
2012-01-01 22:00:00 0.5 16.6
2012-01-01 23:00:00 0.8 15.9 
cuerna.iloc[0]
To       19.3
Ws        0.0
Wd       26.0
P     87415.0
Ig        0.0
Ib        0.0
Id        0.0
Name: 2012-01-01 00:00:00, dtype: float64
cuerna.iloc[0:10]
To Ws Wd P Ig Ib Id
tiempo
2012-01-01 00:00:00 19.3 0.0 26 87415 0 0 0
2012-01-01 01:00:00 18.6 0.0 26 87602 0 0 0
2012-01-01 02:00:00 17.9 0.0 30 87788 0 0 0
2012-01-01 03:00:00 17.3 0.0 30 87554 0 0 0
2012-01-01 04:00:00 16.6 0.0 27 87321 0 0 0
2012-01-01 05:00:00 15.9 0.0 26 87087 0 0 0
2012-01-01 06:00:00 17.0 0.0 27 87096 0 0 0
2012-01-01 07:00:00 18.0 0.0 34 87140 20 151 11
2012-01-01 08:00:00 19.0 0.0 61 87185 164 522 37
2012-01-01 09:00:00 20.0 0.0 95 87229 369 812 58 
cuerna.iloc[-1]
To       15.9
Ws        0.8
Wd       93.0
P     87143.0
Ig        0.0
Ib        0.0
Id        0.0
Name: 2012-01-01 23:00:00, dtype: float64
cuerna.iloc[-1:-10:-2]
To Ws Wd P Ig Ib Id
tiempo
2012-01-01 23:00:00 15.9 0.8 93 87143 0 0 0
2012-01-01 21:00:00 17.0 0.2 85 87080 0 0 0
2012-01-01 19:00:00 17.0 0.0 269 87101 0 0 0
2012-01-01 17:00:00 19.0 0.0 198 87185 219 650 46
2012-01-01 15:00:00 21.3 1.2 176 87287 617 932 74