csv-manager 0.11.0

A simple CSV importer/exporter with plotting capabilities with matplotlib

csv_manager

This is a python module that features three simple classes for reading (class Reader), plotting (class Plotter, using Matplotlib with Latex rendering enabled) for the plots) and filtering (class Database) CSV files. And also a method for writing CSVs.

By using this module, the user avoids the cumbersome repetition of coding a csv reader using the csv python library then making the data in a readable structure for plt.plot(...).

Using Reader and Plotter

An example is written in example/csv_plot_example.py, that showcases what can be done with this module:

from csv_manager.plotter import Plotter
# Plotter inherits the class Reader

plotter = Plotter(num_rows=1, num_columns=2)
# Number of rows and columns for plt.sublots

file1 = 'data_file_1.csv'
file2 = 'data_file_2.csv'

plotter.load(file1, alias='dataset1')
plotter.load(file2, alias='dataset1')
#Both files are loaded in the same `dataset`, if column names collide, the latest ones get "_b" appended to their name

plotter.show_loaded_data()
# prints the loaded datasets. For each dataset, is printed:
# - the source files the data has been loaded from
# - the column names

plotter.get_column_names('dataset1')
# returns the list of column names of the dataset `dataset1`

######################################################

plotter.plot('dataset1', 'time', 'position', 0, 0, label='position $x(t)$', color='red', linestyle=':')
# Starting from " label='save' [...]" the arguments are the **kwargs in https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html
plotter.plot('dataset1', 'time', 'speed', 0, 0, label='speed $v(t)$', color='blue', linestyle='--')

plotter.plot('dataset1', 'time', 'position + sqrt(2/10 * speed)', 0, 1, label='dummy curve from expression')

plotter.plot_data(0, 0, [0, 1, 2], [0, 1, 2], label='dummy data')

plotter.set(0, 0, xlabel='Time ', ylabel='Position')
# Starting from " xlabel='time' [...]" the options that can be set are the **kwargs in https://matplotlib.org/api/axes_api.html

plotter.set(0, 1, xlabel='Time ', ylabel='Dummy data')

plotter.show()

The file example/data_file_1.csv looks like the following:

time position
0 0
1 5
2 20
3 45
4 80
5 125
6 180
7 245
8 320
9 405
10 500

The file example/data_file_2.csv looks like the following:

time speed
0 0
1 3
2 3.6
3 2
4 5
5 8
6 9
7 10
8 9.1
9 8
10 7

Using Database

If you have a folder with lots of CSV files and find it too cumbersome to find the correct ones to plot or read. The class Databse is made for you!

Requirements:

• Follow a specific naming scheme on your CSV files: filename|var1=val1|var2=val2|...|varN=valN.csv where | is a separator that can be different (any string of characters).
• Have all your CSV files in a folder (work if they are in a subfolder of that folder)

Then, what you can do is to create a Database instance with the folder path, and then you can use its method filter_datafiles:

def filter_datafiles(self, file_name_base: str, filter_dict : dict) -> List[DataFile]:

where:

• file_name_base is a string that the file should contain in its filename (the text before the var definitions start)
• filter_dict is a dictionnary that contains (key, val) pairs, both strings, that correspond to varN=valN in the csv files you are looking for.

And this method will return all the files that match your filters.

Dependencies:

• Python Matplotlib
• Python py_expression_eval, can be installed with pip install py_expression_eval
• Latex distribution installed in your computer, can be deactivated in csv_plotter.py by changing the following line plt.rcParams['text.usetex'] = True to plt.rcParams['text.usetex'] = False