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Link: https://github.com/charlesreid1/wifi-data
Link: https://github.com/charlesreid1/wifi-data


==time information: timestamp extraction==
==timestamp extraction==


Timestamps.ipynb - ipython notebook that extracts "first time seen" and uses it as the time marker for each observation. This results in a new dataframe (to csv) that contains one item for each observation listed in a csv file.
Timestamps.ipynb - ipython notebook that extracts "first time seen" and uses it as the time marker for each observation. This results in a new dataframe (to csv) that contains one item for each observation listed in a csv file.


Link: https://github.com/charlesreid1/wifi-data/blob/master/pandas/Timestamps.ipynb
Link: https://github.com/charlesreid1/wifi-data/blob/master/pandas/Timestamps.ipynb
==time series==
now that the time-indexed data is in pandas, we can more easily visualize it. The TimeSeriesPlots ipython notebook plots several quantities directly from the dataframe.
Link: https://github.com/charlesreid1/wifi-data/blob/master/pandas/TimeSeriesPlots.ipynb





Latest revision as of 04:16, 5 March 2016

all the code

The wifi-data repository on Github has all of the code for the operations described here:

Link: https://github.com/charlesreid1/wifi-data

timestamp extraction

Timestamps.ipynb - ipython notebook that extracts "first time seen" and uses it as the time marker for each observation. This results in a new dataframe (to csv) that contains one item for each observation listed in a csv file.

Link: https://github.com/charlesreid1/wifi-data/blob/master/pandas/Timestamps.ipynb

time series

now that the time-indexed data is in pandas, we can more easily visualize it. The TimeSeriesPlots ipython notebook plots several quantities directly from the dataframe.

Link: https://github.com/charlesreid1/wifi-data/blob/master/pandas/TimeSeriesPlots.ipynb