room_temp.py

In [1]: import pandas as pd
In [2]: df1=pd.read_csv("1.csv", index_col=1, parse_dates=True)
In [3]: df2=pd.read_csv("2.csv", index_col=1, parse_dates=True)
In [4]: df1.head(5)
Out[4]: 
                     id   temp  pir  reed
timestamp                                
2012-01-16 16:46:28   0  23.25    1     0
2012-01-16 16:46:29   1  23.10    1     0
2012-01-16 16:46:30   2  23.20    0     0
2012-01-16 16:46:30   3  23.25    0     0
2012-01-16 16:46:31   4  23.25    1     0

[5 rows x 4 columns]

In [5]: df2.head(5)
Out[5]: 
                     id   temp  pir  reed
timestamp                                
2012-01-16 16:46:27   0  19.90    0     1
2012-01-16 16:46:28   1  19.95    0     1
2012-01-16 16:46:29   2  20.00    0     1
2012-01-16 16:46:30   3  19.70    0     1
2012-01-16 16:46:31   4  20.00    0     1

[5 rows x 4 columns]

In [6]: df1_temp_downsampled=df1["temp"].resample(rule="1min",how="mean")
In [7]: df2_temp_downsampled=df2["temp"].resample(rule="1min",how="mean")
In [8]: df1_temp_downsampled.head(5)
Out[8]: 
timestamp
2012-01-16 16:46:00    23.185366
2012-01-16 16:47:00    23.122436
2012-01-16 16:48:00    23.068590
2012-01-16 16:49:00    23.053896
2012-01-16 16:50:00    23.061538
Freq: T, Name: temp, dtype: float64

In [9]: %matplotlib qt
In [10]: df1_temp_downsampled.plot()
Out[10]: <matplotlib.axes.AxesSubplot at 0x1c763e10>

In [11]: df2_temp_downsampled.plot()
Out[11]: <matplotlib.axes.AxesSubplot at 0x1c763e10>

In [12]: import matplotlib.pyplot as plt

In [16]: df2_temp_downsampled.plot(label="Room 2")
Out[16]: <matplotlib.axes.AxesSubplot at 0x1cf3c110>

In [17]: df1_temp_downsampled.plot(label="Room 1")
Out[17]: <matplotlib.axes.AxesSubplot at 0x1fe0e690>

In [18]: df2_temp_downsampled.plot(label="Room 2")
Out[18]: <matplotlib.axes.AxesSubplot at 0x1fe0e690>

In [19]: plt.legend()
Out[19]: <matplotlib.legend.Legend at 0x1cf1bbd0>

In [20]: plt.ylabel("Temp (Celsius)")
Out[20]: <matplotlib.text.Text at 0x1fe90590>

In [21]: plt.savefig("temp_comparison.png")

In [24]: import bearcart

In [25]: df_temp = pd.DataFrame({'Room 1':df1_temp_downsampled, 'Room 2':df2_temp_downsampled})

In [26]: df_temp.head(5)
Out[26]: 
                        Room 1     Room 2
timestamp                                
2012-01-16 16:46:00  23.185366  19.966667
2012-01-16 16:47:00  23.122436  19.957692
2012-01-16 16:48:00  23.068590  19.956494
2012-01-16 16:49:00  23.053896  19.968590
2012-01-16 16:50:00  23.061538  19.972388

[5 rows x 2 columns]

In [28]: html_path = r'index.html'

In [29]: data_path = r'data.json'

In [30]: js_path = r'rickshaw.min.js'

In [31]: css_path = r'rickshaw.min.css'

In [36]: vis = bearcart.Chart(df_temp[df_temp.index.month==4].resample(rule="15min"))

In [37]: vis.create_chart(html_path=html_path, data_path=data_path,
                 js_path=js_path, css_path=css_path)