Skip to main content

A wordy but intuitive plotting library.

Project description

Plotxel

Control your plots down to the pixel!
Ever have trouble moving a chart to the right? Moving your axis up? Getting rid of ticks? Then try out Plotxel!

It's wordy, slow, and unnecessary 99% of the time. But that 1%, you'll be glad you have Plotxel.

Installation

pip3 install plotxel

Example

Example Image

from plotxel import Plotxel, Axis

x = Plotxel()  # our main drawing canvas in x, y

# add some data as a series. The series name, the x data, and y data
series1 = [i for i in range(10)]
x.add_data('series1', series1, series1)
x.add_data('series2', [1, 2, 3, 4, 5, 10], [5, 2, 1, 4, 3, 10])
x.add_data('series3', [10, 5, 4, 3, 2, 1], [5, 2, 1, 4, 3, 10])

# left plot -- its name, type, and data it's linked to
plot1 = x.add_drawable("plot1", "Scatter", ["series1", 'series2', 'series3'])
plot1.title = 'Analysis of Goose Encounters'
plot1.pos = [60, 50]
plot1.title_offset = 23
plot1.marker_opacity = {.5}  # this must be a set so it can iterate through data. Will make this more intuitive

# right plot and its position. Same data as plot1
plot2 = x.add_drawable("plot2", "Scatter", "series1")
# set a bunch of attributes at once!
plot2.setattrs(
    ylim=[-1, 10],
    xlim=[-1, 10],
    pos=[450, 50],
    marker_shape='square',
    marker_fill_color=(255, 0, 0),
    title='Analysis of Goose Encounters (red)',
    line_width = 0
)

# add some axes, and link them to our plots. It will copy the size, position, scale, and limits of whichever plot it is linked to
ax1 = x.add_drawable("ax1", 'YAxis', link_to="plot1")
ax1.axis_offset = 10
ax1.title_offset = 25  # distance from the ticks. Will have an auto feature in the future!
ax1.title = "Near Death Experiences With Geese"

# all other axes, let's put them flush with the graph by changing the default
# defaults are copied at the time the object is initialized, so this won't affect ax1
Axis.defaults['axis_offset'] = -1
ax1b = x.add_drawable('ax1b', 'XAxis', link_to='plot1')

# you can keep setting attributes in bulk
ax1r = x.add_drawable('ax1r', 'YAxis', link_to='plot1', title_offset=20)
ax1r.setattrs(
    side='right',
    title_offset=20,
    title='Ax1 Right Title'
)

ax1t = x.add_drawable('ax1t', 'XAxis', link_to='plot1')
ax1t.setattrs(
    side='top',
    title=''
)

# or use the constructor!
x.add_drawable("ax2", 'YAxis', link_to="plot2", title_offset=20, side='right', axis_offset=10)

ax3 = x.add_drawable("ax3", 'XAxis', link_to="plot2")
ax3.setattrs(
    side='bottom',
    axis_offset=10,
    title="Number of Freaking Geese",
)


# I think I would prefer axes to be blue!
Axis.defaults['color'] = (0, 0, 255)

# let's add some bar chart data. Since it's a vertical bar chart, we will pull Y data
# the labels aren't implemented quite yet
x.add_data('bar_data', ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday'], [1, 9, 4, 5, 3, 6, 2])
x.add_data('bar_data2', ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday'], [1, 7, 4, 3, 4, 5, 1])
x.add_data('bar_data3', ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday'], [-3, 14, 2, 1, 2, 7, 9])

plot3 = x.add_drawable('bar1', 'Bar', ['bar_data', 'bar_data2', 'bar_data3'])
# or unpack a dict
plot3_attrs = {
    'pos': (150, 300),
    'dim': (500, 150),
    'ylim': [-5, 15],
    'group_spacing': 30,
    'bar_spacing': 0,
    'title': 'Safely Navigating Geese'
}
plot3.setattrs(**plot3_attrs)

x.add_drawable('ax4', 'YAxis', link_to="bar1", title='Likelihood of Goose Attack', title_offset=25)
# x.add_drawable('ax5', 'XAxis', link_to='bar1', title='Day of Week', title_offset=5)

# coming soon, Jupyter magic!
# x.anti_aliasing=False
x.show()

# or for SVG
# svg_html = x.draw()

# or for image  in BytesIO / save to filename
# x.render(filename='example2.png')

This program is being developed based on my own needs, and unfortunately I don't do a lot of plotting today, therefore I don't need a lot of features.

In any case, I'll be prioritizing features, up next is bar charts and histograms!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

plotxel-0.0.7.tar.gz (15.6 kB view details)

Uploaded Source

Built Distribution

plotxel-0.0.7-py3-none-any.whl (16.4 kB view details)

Uploaded Python 3

File details

Details for the file plotxel-0.0.7.tar.gz.

File metadata

  • Download URL: plotxel-0.0.7.tar.gz
  • Upload date:
  • Size: 15.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/41.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.4

File hashes

Hashes for plotxel-0.0.7.tar.gz
Algorithm Hash digest
SHA256 adace3eb04bdc49464b7d60758858abae8ffdfa55456de75bf44ad80f1544c86
MD5 24c24667898a2774b52dcb4bf2217400
BLAKE2b-256 a8419bebb488d7cba2d659f99e48009e58541e10db75e61f72a179c39d4c72b4

See more details on using hashes here.

File details

Details for the file plotxel-0.0.7-py3-none-any.whl.

File metadata

  • Download URL: plotxel-0.0.7-py3-none-any.whl
  • Upload date:
  • Size: 16.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/41.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.4

File hashes

Hashes for plotxel-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 88d6fded09cf571150f6f0f4c0a3a82862fbc66e7680dd6c3efd219393b99ec6
MD5 d6e9764270b80df856c88780d77b4f6d
BLAKE2b-256 b63ffa21e20f809ab647b5de98f90154232ce06f10bdfed08f0e7fd341cbac35

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page