plottoolbox - Quick Guide
The plottoolbox is a Python script to manipulate time-series on the command line or by function calls within Python. Uses pandas (http://pandas.pydata.org/) or numpy (http://numpy.scipy.org) for any heavy lifting.
Requirements
pandas - on Windows this is part scientific Python distributions like Python(x,y), Anaconda, or Enthought.
Installation
Should be as easy as running pip install plottoolbox or easy_install plottoolbox at any command line. Not sure on Windows whether this will bring in pandas, but as mentioned above, if you start with scientific Python distribution then you shouldn’t have a problem.
Usage - Command Line
Just run ‘plottoolbox –help’ to get a list of subcommands:
usage: plottoolbox [-h]
{autocorrelation, bar, bar_stacked, barh, barh_stacked,
bootstrap, boxplot, double_mass, heatmap, histogram,
kde, kde_time, lag_plot, lognorm_xaxis, lognorm_yaxis,
norm_xaxis, norm_yaxis, probability_density,
scatter_matrix, target, taylor, time, weibull_xaxis,
weibull_yaxis, xy, about} ...
positional arguments:
{autocorrelation, bar, bar_stacked, barh, barh_stacked, bootstrap,
boxplot, double_mass, heatmap, histogram, kde, kde_time, lag_plot,
lognorm_xaxis, lognorm_yaxis, norm_xaxis, norm_yaxis,
probability_density, scatter_matrix, target, taylor, time, weibull_xaxis,
weibull_yaxis, xy, about}
autocorrelation
Autocorrelation plot.
bar
Bar plot, sometimes called a "column" plot.
bar_stacked
Stacked vertical bar, sometimes called a stacked column plot.
barh
Bar plot, sometimes called a "column" plot.
barh_stacked
Horizontal stacked bar plot.
bootstrap
Bootstrap plot randomly selects a subset of the imput time-series.
boxplot
Box and whiskers plot.
double_mass
Double mass curve - cumulative sum of x against cumulative sum of y.
heatmap
2D heatmap of daily data.
histogram
Histogram.
kde
Kernel density estimation of probability density function.
kde_time
A time-series plot with a kernel density estimation (KDE) plot.
lag_plot
Lag plot.
lognorm_xaxis
Log-normal x-axis.
lognorm_yaxis
Log-normal y-axis.
norm_xaxis
Normal x-axis.
norm_yaxis
Normal y-axis.
probability_density
Probability plot.
scatter_matrix
Plots all columns against each other in matrix of plots.
target
Creates a "target" diagram to plot goodness of fit.
taylor
Taylor diagram to plot goodness of fit.
time
Time-series plot.
weibull_xaxis
Weibull x-axis.
weibull_yaxis
Weibull y-axis.
xy
Creates an 'x,y' plot, also known as a scatter plot.
about
Display version number and system information.
optional arguments:
-h, --help show this help message and exit
The default for all of the subcommands is to accept data from stdin (typically a pipe). If a subcommand accepts an input file for an argument, you can use “–input_ts=input_file_name.csv”, or to explicitly specify from stdin (the default) “–input_ts=’-‘”.
For the subcommands that output data it is printed to the screen and you can then redirect to a file.
Usage - API
You can use all of the command line subcommands as functions. The function signature is identical to the command line subcommands. The return is always a PANDAS DataFrame. Input can be a CSV or TAB separated file, or a PANDAS DataFrame and is supplied to the function via the ‘input_ts’ keyword.
Simply import plottoolbox:
from plottoolbox import plottoolbox # Then you could call the functions plt = plottoolbox.time(input_ts='tests/test_fill_01.csv')
1 maintainer
Metadata
1 maintainer
Release files for plottoolbox 102.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| plottoolbox-102.1.1.tar.gz | 4.4 MB | Details |
Release files / plottoolbox-102.1.1.tar.gz
| Download URL | plottoolbox-102.1.1.tar.gz |
|---|---|
| Size | 4.4 MB |
| Tags | Source |
|
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