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Chapter 1 - Reading data from a CSV
===================================
There are several ways to read data from a CSV file. The following are the most
common ways:
- Native reading
- the `CSV module <https://docs.python.org/3/library/csv.html>`_
- the `numpy module <https://www.numpy.org>`_
- the `pandas module <https://pandas.pydata.org/>`_
In this chapter, you will learn to use pandas to read and filter CSV data.
In addition, you could pass the data file through a command-line option to your
script.
The following python script, :code:`main.py`, demonstrates how to do it:
.. literalinclude:: datavisualize1/main.py
:language: python
:linenos:
:lines: 40-
The Python script uses the :code:`argparse` module to accept and parse input
from the command line. It then uses the input, which in this case is the filename,
to read and print data to the prompt.
Try running the script in the following way to check if you get desired output:
::
$python datavisualize1/main.py -f all_hour.csv
time latitude longitude depth ... magNst status locationSource magSource
0 2019-01-10T12:11:24.810Z 34.128166 -117.775497 4.46 ... 6.0 automatic ci ci
1 2019-01-10T12:04:26.320Z 19.443333 -155.615997 0.72 ... 6.0 automatic hv hv
2 2019-01-10T11:57:48.980Z 33.322500 -116.393167 4.84 ... 11.0 automatic ci ci
3 2019-01-10T11:52:09.490Z 38.835667 -122.836670 1.28 ... 7.0 automatic nc nc
4 2019-01-10T11:25:44.854Z 65.108200 -149.370100 20.60 ... NaN automatic ak ak
5 2019-01-10T11:25:23.786Z 69.151800 -144.497700 10.40 ... NaN reviewed ak ak
6 2019-01-10T11:16:11.761Z 61.331800 -150.070800 20.10 ... NaN automatic ak ak
[7 rows x 22 columns]
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