Merging.ipynb

Kernel: Python 3 (Anaconda)

import numpy as np
import pandas as pd

column_names = ['Time','ppm']
year1CO2 = pd.read_csv('Netatmo2016CO2ONLY.csv', parse_dates=True, index_col=0, names=column_names)
year1CO2.head()

	ppm
Time
2016-02-19 13:26:00	NaN
2016-02-19 13:27:00	718.0
2016-02-19 13:27:00	NaN
2016-02-19 13:31:00	337.0
2016-02-19 13:36:00	332.0

column_names = ['Time','ppm']
year2CO2= pd.read_csv('Netatmo2017CO2ONLY.csv', parse_dates=True, index_col=0, names=column_names)
year2CO2.to_csv('2017CO2ONLY.csv')

year2 = pd.read_csv('2017CO2ONLY.csv', parse_dates=True, index_col=0,)
#year2.head()

column_names = ['Time','ppm']
year1CO2= pd.read_csv('Netatmo2016CO2ONLY.csv', parse_dates=True, index_col=0, names=column_names)
year1CO2.to_csv('2016CO2ONLY.csv')

year1 =  pd.read_csv('2016CO2ONLY.csv', parse_dates=True, index_col=0,)
year1.head()

	ppm
Time
2016-02-19 13:26:00	NaN
2016-02-19 13:27:00	718.0
2016-02-19 13:27:00	NaN
2016-02-19 13:31:00	337.0
2016-02-19 13:36:00	332.0

year1.head()

	ppm
Time
2016-02-19 13:26:00	NaN
2016-02-19 13:27:00	718.0
2016-02-19 13:27:00	NaN
2016-02-19 13:31:00	337.0
2016-02-19 13:36:00	332.0

year1.tail()

	ppm
Time
2016-12-31 23:35:00	483.0
2016-12-31 23:40:00	485.0
2016-12-31 23:45:00	489.0
2016-12-31 23:50:00	475.0
2016-12-31 23:55:00	475.0

year2.tail()

	ppm
Time
2017-02-12 18:27:00	484
2017-02-12 18:32:00	486
2017-02-12 18:37:00	469
2017-02-12 18:42:00	485
2017-02-12 18:47:00	480

year2.head()