scatterbin
Adjustable binning of scatter plot data
pip install scatterbin
Requires
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
from scipy import stats
import sys
import scatterbin
scatterbin.plot(data)
where data is an array 2D array of the x and y data.
See src/scatterbin/demos.ipynb for examples
Parameters
data : obj
The data in the form of a 2D array
two_panel : bool (default : False)
The default is to plot the binned data in the scatter plot. If set to
True this will plot these in a panel below.
width : float (default : 7)
The width of the plot.
height : float (default : 5)
The height of the plot.
height_ratios : [float, float] (default : [1,0.5])
When two_panel = True, the height ratios of the two panels.
fs : float (default : 12)
The font size used in the plot.
aw : float (default : 2)
Axis widths
aw : float (default : 7)
Axis padding
point_sym : MarkerStyle (default : 'o')
The scatter plot marker
point_s : float (default : 20)
Point size in scatter plots
point_ec : str (default :'r')
The edge colour of the points
point_cc : str (default :'r')
The face colour of the points
point_top : bool (default : False)
If True plots the scatter plots over the binned data
in the single panel plot.
alpha : float (default : 1)
The transparency of the points
lrot : float (default : 0)
Axis label rotation angle
min_space : int (default : 5)
Number of minor ticks per major tick interval
xlabel_off : bool (default : True)
If True this removes the x-axis labels
ylabel_off : bool (default : True)
If True this removes the y-axis labels
xlabel : str (default : 'x')
The x-axis label
ylabel : str (default : 'x')
The y-axis label
pvalue : bool (default : False)
If True this will show the p-value of the distribution
according to Kendall's tau
leg_scale: float (default : 0.8)
The scaling of the legend text in relation to fs
leg_loc : str (default: 'upper left')
The location of the legend
nbins : int (default : 5)
The number of bins for the binning
equal_span : str (default : 'x')
The type of binning
equal_span = 'x' : each bin spans the same x-range
equal_span = 'n' : quantile binning - each bin
contains an equal number of
points and the x-error bars
show the standard deviation
equal_span = 'nx' : shows the mean of the quantile
binning, but the x-error bars show
the range of the binning
inc_strays : bool (default : False)
The quantile binning will have some stray points
left over if the number of points is not divisible
by the number of bins. Setting this to True includes
these stray points in the last bin
SE : bool (default : False)
If True the error bars show the standard error rather
than the default standard deviation
blw : float (default : 2)
The line width of the error bars
bcol : str (default : 'k')
The colour of the error bars
capsize : float (default : 5)
The cap size of the error bars
hc : bool (default : False)
hc = True saves a hard copy
plot_form : str (default : 'png')
The format of the hard copy
plot_name : str (default : 'scatterbin')
The name of the hard copy
Metadata
Release files for scatterbin 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scatterbin-0.0.2.tar.gz | 6.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scatterbin-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.1 kB
Release files / scatterbin-0.0.2.tar.gz
| Download URL | scatterbin-0.0.2.tar.gz |
|---|---|
| Size | 6.7 kB |
| Tags | Source |
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| Download URL | scatterbin-0.0.2-py3-none-any.whl |
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| Size | 11.4 kB |
| Tags | Python 3 |
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