Modules¶

fcp.py¶

fivecentplots.fcp.axes()¶

ax_edge_color (hex color string): outer edge color of plot area;: default: #aaaaaa; ex: None
ax_fill_color (hex color string): inner fill color of plot area |: x-axis: [‘linear’, ‘logx’, ‘semilogx’] | y-axis: [‘linear’, ‘logx’, ‘semilogx’] | both: [‘loglog’, ‘log’] | other: [‘symlog’, ‘logit’]; default: #eaeaea; ex: None
ax_size (list of ints): width, height of plot area; default: [400,: 400]; ex: None
twin_x (boolean): enable/disable a secondary y-axis (x-axis is: “twinned” or duplicated across two y-axes); default: False; ex: see online docs
twin_y (boolean): enable/disable a secondary x-axis (y-axis is: “twinned” or duplicated across two x-axes) | Note: wrap plots cannot be used when twin_y == True; default: False; ex: see online docs
xmin (float|list of floats|None): minimum x-values; can use a list for: each subplot; default: None; ex: see online docs
x2min (float|list of floats|None): minimum x-values; can use a list: for each subplot; default: None; ex: see online docs
xmax (float|list of floats|None): maximum x-values; can use a list for: each subplot; default: None; ex: see online docs
x2max (float|list of floats|None): maximum x-values for secondary: axis; can use a list for each subplot; default: None; ex: see online docs
ymin (float|list of floats|None): minimum y-values; can use a list for: each subplot; default: None; ex: see online docs
y2min (float|list of floats|None): minimum y-values for secondary: axis; can use a list for each subplot; default: None; ex: see online docs
ymax (float|list of floats|None): maximum y-values; can use a list for: each subplot; default: None; ex: see online docs
y2max (float|list of floats|None): maximum y-values for secondary: axis; can use a list for each subplot; default: None; ex: see online docs

fivecentplots.fcp.bar(*args, **kwargs)¶

Main bar chart plotting function At minimum, it requires a pandas DataFrame with at least one column for the y axis. Plots can be customized and enhanced by passing keyword arguments. Default values that must be defined in order to generate the plot are pulled from the fcp_params default dictionary :param df: DataFrame containing data to plot :type df: DataFrame :param x: name of x column in df :type x: str :param y: name or list of names of y column(s) in df :type y: str|list

Keyword Arguments: online docs (see) –
Returns: plots

fivecentplots.fcp.boxplot(*args, **kwargs)¶

Main boxplot plotting function At minimum, it requires a pandas DataFrame with at least one column for the y axis. Plots can be customized and enhanced by passing keyword arguments. Default values that must be defined in order to generate the plot are pulled from the fcp_params default dictionary

Parameters

df (DataFrame) – DataFrame containing data to plot
y (str|list) – column name in df to use for the box(es)

Keyword Arguments

Dividers (Box) –

box_divider_on (boolean): toggle divider lines between groups on/off;
default: True; ex: None

box_divider_color (str): line color; default: #bbbbbb; ex: None
Range Lines (Box) –

box_range_lines_on (boolean): toggle range lines on/off; default:
True; ex: None

box_range_lines_color (str): line color; default: #cccccc; ex: None box_range_lines_style (str): horizontal lines at the end of the range;

default: -; ex: None

box_range_lines_style2 (str): vertical lines connecting the horizontal
lines at the end of the range; default: –; ex: None
Stat Lines (Box) –

box_stat_line_on (boolean): toggle divider lines between groups
on/off; default: True; ex: None

box_stat_line (str): set the statistic for the connecting line;
default: mean; ex: None

box_stat_line_color (str): line color; default: #666666; ex: None

fivecentplots.fcp.cbar()¶

cbar (boolean): toggle colorbar on/off for contour and heatmap plots;: default: False; ex: see online docs
size (int): cbar width (height will match the height of the axes);: default: 30; ex: nan

fivecentplots.fcp.contour(*args, **kwargs)¶

Main contour plotting function At minimum, it requires a pandas DataFrame with at least three columns and three column names for the x, y, and z axis. Plots can be customized and enhanced by passing keyword arguments as defined below. Default values that must be defined in order to generate the plot are pulled from the fcp_params default dictionary

Parameters

df (DataFrame) – DataFrame containing data to plot
x (str|list) – name of list of names of x column in df
y (str|list) – name or list of names of y column(s) in df
z (str) – name of z column(s) in df

Keyword Arguments

bar (Color) –

cbar (boolean): toggle colorbar on/off for contour and heatmap plots;: default: False; ex: see online docs
size (int): cbar width (height will match the height of the axes);: default: 30; ex: nan

fivecentplots.fcp.deprecated(kwargs)¶: Fix deprecated keyword args

fivecentplots.fcp.figure()¶: dpi (int): dots per inch; default: 100; ex: None

fivecentplots.fcp.fit()¶

fit (int): polynomial degree for the fit; default: None; ex: see: online docs
fit_color (hex color str): color of the fit line; default: #000000;: ex: None
fit_eqn (boolean): display the fit equation on the plot; default:: False; ex: None
fit_font_size (float): font size of the fit eqn and rsq value;: default: 12; ex: None
fit_padding (int): padding in pixels from the top of the plot to the: location of the fit eqn; default: 10; ex: None
fit_range_x (list): compute the fit only over a given range of: x-values; default: None; ex: see online docs
fit_range_y (list): compute the fit only over a given range of: y-values; default: None; ex: nan
fit_rsq (boolean): display the rsq of the fit on the plot; default:: False; ex: None

fivecentplots.fcp.gridlines()¶

fivecentplots.fcp.heatmap(*args, **kwargs)¶

Main heatmap plotting function At minimum, it requires a pandas DataFrame with at least three columns and three column names for the x, y, and z axis. Plots can be customized and enhanced by passing keyword arguments as defined below. Default values that must be defined in order to generate the plot are pulled from the fcp_params default dictionary

Parameters

df (DataFrame) – DataFrame containing data to plot
x (str|list) – name of list of names of x column in df
y (str|list) – name or list of names of y column(s) in df
z (str) – name of z column(s) in df

Keyword Arguments

bar (Color) –

cbar (boolean): toggle colorbar on/off for contour and heatmap plots;: default: False; ex: see online docs
size (int): cbar width (height will match the height of the axes);: default: 30; ex: nan

fivecentplots.fcp.help()¶

fivecentplots.fcp.hist(*args, **kwargs)¶: Histogram plot

fivecentplots.fcp.kw_header(val, indent=' ')¶: Indent header names

fivecentplots.fcp.kw_print(kw)¶: Print friendly version of kw dicts

fivecentplots.fcp.labels()¶

fivecentplots.fcp.legend()¶

legend (str): name of a DataFrame column to use for grouping; default:: None; ex: see online docs
location (int | str): location of legend (at this time only outside of: the plot is available!): | * 0 | “outside” = outside of plot on right side | * 1 | “upper right” = upper right inside corner | * 2 | “upper left = upper left inside corner | * 3 | “lower left” = lower left inside corner | * 4 | “lower right” = lower right inside corner | * 5 | “right” | * 6 | “center left” | * 7 | “center right” | * 8 | “lower center” | * 9 | “upper center” | * 10 | “center” ; default: 0; ex: None
legend_marker_alpha (float): alpha of the markers in the legend only;: default: 1; ex: see online docs
legend_marker_size (float): marker size in legend only; default: same: as marker_size; ex: see online docs
legend_points (int): number of points for each legend value; default:: 1; ex: None
legend_title (str): legend title text; default: defaults to legend: column name; ex: None

fivecentplots.fcp.lines()¶

colors (hex color str or list of hex color strs): colors to use for: lines and markers; default: default list; ex: see online docs

lines (boolean): toggle line visibility; default: True; ex: None

fivecentplots.fcp.markers()¶

markers (boolean or list of str characters): if False, turns off: markers on the plot | if a list of characters, sets the markers to be used (one marker type per curve or data set); default: default marker list; ex: see online docs
marker_fill (boolean): turn on/off marker fill; default: False; ex:: None
marker_edge_color (hex color str): set the marker edge color; default:: match the line color scheme; ex: None
marker_edge_width (float): set the marker edge width; default: 1.5;: ex: None
marker_fill_color (hex color str): set the marker fill color (only: rendered if marker_fill=True); default: True; ex: None
marker_jitter (boolean): add a random offset or jitter to the points: around their x-value (useful for box plots); default: True for boxplots | False for all other plot types; ex: None
marker_size (float): size of the markers (can be specified uniquely: from the legend marker size); default: 7; ex: see online docs

fivecentplots.fcp.nq(*args, **kwargs)¶: Plot normal quantiles of a data set

fivecentplots.fcp.paste_kwargs(kwargs)¶

Get the kwargs from contents of the clipboard in ini file format

Parameters: kwargs (dict) – originally inputted kwargs
Returns: kwargs

fivecentplots.fcp.plot(*args, **kwargs)¶: XY plot

fivecentplots.fcp.plot_bar(data, layout, ir, ic, df_rc, kwargs)¶

Plot data as boxplot

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

fivecentplots.fcp.plot_box(dd, layout, ir, ic, df_rc, kwargs)¶

Plot data as boxplot

Parameters

dd (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

Keywords:

fivecentplots.fcp.plot_conf_int(ir, ic, iline, data, layout, df, x, y, twin)¶

fivecentplots.fcp.plot_contour(data, layout, ir, ic, df_rc, kwargs)¶

Plot contour data

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

fivecentplots.fcp.plot_fit(data, layout, ir, ic, iline, df, x, y, twin, leg_name, ngroups)¶

Plot a fit line

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
iline (int) – iterator
df (pd.DataFrame) – input data
x (str) – x-column name
y (str) – y-column name
twin (bool) – denote twin axis
leg_name (str) – legend value
ngroups (int) – number of groups in this data set

fivecentplots.fcp.plot_heatmap(data, layout, ir, ic, df_rc, kwargs)¶

Plot heatmap data data

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

fivecentplots.fcp.plot_hist(data, layout, ir, ic, df_rc, kwargs)¶

Plot data as histogram

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

fivecentplots.fcp.plot_nq(data, layout, ir, ic, df_rc, kwargs)¶

Plot data as normal quantiles by sigma

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

fivecentplots.fcp.plot_ref(ir, ic, iline, data, layout, df, x, y)¶: Plot a reference line

fivecentplots.fcp.plot_stat(ir, ic, iline, data, layout, df, x, y, leg_name=None, twin=False)¶: Plot a line calculated by stats

fivecentplots.fcp.plot_xy(data, layout, ir, ic, df_rc, kwargs)¶

Plot xy data

Parameters

data (obj) – Data object
layout (obj) – layout object
ir (int) – current subplot row number
ic (int) – current subplot column number
df_rc (pd.DataFrame) – data subset
kwargs (dict) – keyword args

fivecentplots.fcp.plotter(plot_func, **kwargs)¶

Main plotting function

UPDATE At minimum, it requires a pandas DataFrame with at least two columns and two column names for the x and y axis. Plots can be customized and enhanced by passing keyword arguments as defined below. Default values that must be defined in order to generate the plot are pulled from the fcp_params default dictionary

Parameters

df (DataFrame) – DataFrame containing data to plot
x (str) – name of x column in df
y (str|list) – name or list of names of y column(s) in df

Keyword Arguments

UPDATE –

Returns

plots

fivecentplots.fcp.ref_line()¶

color (hex color str): color of the reference line; default: #000000;: ex: see online docs
text (str): legend text for the reference line; default: “Ref Line”;: ex: nan

fivecentplots.fcp.set_theme(theme=None)¶: Select a “defaults” file and copy to the user directory

fivecentplots.fcp.tick_labels()¶

fivecentplots.fcp.ticks()¶

ticks_<major|minor>_color (hex color string): tick color; default:: #ffffff; ex: None
ticks_major_increment (float): for major ticks only, the increment: between tick marks; default: nan; ex: see online docs
ticks_major_length (float): the length in pixels of the major tick: lines; default: 6.2; ex: None
ticks_minor_length (float): the length in pixels of the minor tick: lines; default: 4.2; ex: None
tick_minor_number (int): enable primary y-axis range sharing across: all subplots; default: True; ex: see online docs
ticks_major_width (float): thickness or edge width of a major tick: mark; default: 2.2; ex: None
ticks_minor_width (float): thickness or edge width of a minor tick: mark; default: 1.3; ex: None

fivecentplots.fcp.ws()¶

ws_label_col (int): col label to top edge of axes window; default: 10;: ex: None
ws_label_row (nan): row label to right edge of axes window; default:: 10; ex: None

ws_col (nan): space between columns; default: 30; ex: None ws_row (nan): space between rows; default: 30; ex: None ws_fig_label (nan): left figure edge to label_y; default: 10; ex: None ws_leg_fig (nan): right legend edge to right figure edge; default: 10;

ex: None

ws_fig_ax (nan): top figure edge to top edge of axes with figure title: disabled; default: 20; ex: None
ws_fig_title (nan): top figure edge to top of figure title; default:: 10; ex: None
ws_label_tick (nan): space between axis label and tick labels;: default: 10; ex: None
ws_leg_ax (nan): right edge of axes to left edge of legend box;: default: 20; ex: None
ws_ticks_ax (nan): space between tick labels and axes; default: 5; ex:: None
ws_title_ax (nan): bottom edge of title to top edge of axes window;: default: 10; ex: None
ws_ax_fig (nan): right edge of axes to right edge of figure with: legend disabled; default: 30; ex: None
ws_tick_tick_minimum (nan): minimum space between consecutive ticks;: default: 10; ex: None
ws_ax_box_title (nan): right edge of axes to right edge of box title: text ; default: 10; ex: None

data.py¶

exception fivecentplots.data.AxisError(*args, **kwargs)¶

class fivecentplots.data.Data(plot_func='xy', **kwargs)¶

ax_limit_pad(**kwargs)¶: Set padding limits for axis

check_df(df)¶: Validate the dataframe

check_group_columns(group_type, col_names)¶

Check wrap/row/column grouping variables for errors

Parameters

group_type (str) – type of grouping (row, col, leg, wrap)
col_name (str) – name of the column by which to group

check_group_errors()¶: Check for common errors related to grouping keywords

check_group_matching(group1, group2)¶

Check to make sure certain group column values are not the same

Parameters

group1 (str) – attr name of first grouping column
group2 (str) – attr name of second grouping column

check_xyz(xyz)¶: Validate the name and column data provided for x, y, and/or z :param xyz: name of variable to check :type xyz: str

get_all_groups(df)¶

Generator to get all possible allowed groups of data

Parameters: df –

Returns:

get_box_index_changes()¶

Make a DataFrame that shows when groups vals change; used for grouping labels

Parameters

df (pd.DataFrame) – grouping values
num_groups (int) – number of unique groups

Returns

new DataFrame with 1’s showing where group levels change for each row of df

get_conf_int(df, x, y, **kwargs)¶

Calculate and draw confidence intervals around a curve

Parameters

df –
x –
y –
ax –
color –
kw –

Returns:

get_data_range(ax, df, ir, ic)¶

Determine the min/max values for a given axis based on user inputs

Parameters

axis (str) – x, x2, y, y2, z
df (pd.DataFrame) – data table to use for range calculation

Returns

min, max tuple

get_data_ranges(ir, ic)¶

Get the data ranges

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

get_data_ranges_bar(ir, ic)¶

Get the data ranges for bar plot data

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

get_data_ranges_hist(ir, ic)¶

Get the data ranges

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

get_df_figure()¶

Generator to subset the main DataFrame based on fig_item grouping

Parameters

fig_item (str) – figure grouping value
kw (dict) – kwargs dict

Returns

DataFrame subset

get_fig_groupings()¶: Determine the figure grouping levels

get_fit_data(ir, ic, df, x, y)¶

Make columns of fitted data

Parameters

df (pd.DataFrame) – main DataFrame
x (str) – x-column name
y (str) – y-column name

Returns

updated DataFrame and rsq (for poly fit only)

get_legend_groupings(df)¶

Determine the legend groupings

Parameters: df (pd.DataFrame) – data being plotted
Returns: updated kwargs dict

get_plot_data(df)¶

Generator to subset into discrete sets of data for each curve

Parameters: df (pd.DataFrame) – main DataFrame
Returns: subset

get_rc_groupings(df)¶

Determine the row and column or wrap grid groupings

Parameters: df (pd.DataFrame) – data being plotted; usually a subset of self.df_all

get_rc_subset(df, ranges=False)¶

Subset the data by the row/col values

Parameters: df (pd.DataFrame) – main DataFrame
Returns: subset DataFrame

get_stat_data(df, x, y)¶

Get a stat subset from input data

Parameters

df (pd.DataFrame) – input data
x (str) – x-column name
y (str) – y-column name

property groupers¶: Get all grouping values

see()¶: Prints a readable list of class attributes

swap_xy()¶: Swap the x and y axis

transform()¶: Transform x, y, or z data by unique group

exception fivecentplots.data.DataError(*args, **kwargs)¶

exception fivecentplots.data.GroupingError(*args, **kwargs)¶

layout.py¶

class fivecentplots.engines.layout.BaseLayout(plot_func, data, **kwargs)¶

add_box_labels(ir, ic, dd)¶

add_hvlines(ir, ic)¶

add_legend()¶

close()¶

format_legend_values()¶: Reformat legend values

from_list(base, attrs, name, kwargs)¶

Supports definition of object attributes for multiple axes using a list

Index 0 is always ‘x’ Index 1 is always ‘y’ Index 2 is for twinned axes

Parameters

base (Element) – object class
attrs (list) – attributes to check from the base class
name (str) – name of the base class
kwargs (dict) – keyword dict

Returns

updated kwargs

get_axes()¶: Return list of active axes

init_white_space(**kwargs)¶: Set the default spacing parameters (plot engine specific) :param kwargs: input args from user

make_figure()¶

make_kwargs(element, pop=[])¶

plot_box(ir, ic, data, **kwargs)¶

Plot boxplot data

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
data (pd.DataFrame) – data to plot

Keyword Arguments

kwargs allowed by the plotter function selected (any) –

Returns

return the box plot object

plot_contour(ax, df, x, y, z, ranges)¶: Plot a contour plot

plot_heatmap(ax, df, x, y, z, ranges)¶

Plot a heatmap

Parameters

ax (mpl.axes) – current axes obj
df (pd.DataFrame) – data to plot
x (str) – x-column name
y (str) – y-column name
z (str) – z-column name
range (dict) – ax limits

plot_hist(ir, ic, iline, df, x, y, leg_name, data, zorder=1, line_type=None, marker_disable=False)¶

plot_line(ir, ic, x0, y0, x1=None, y1=None, **kwargs)¶

Plot a simple line

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
x0 (float) – min x coordinate of line
x1 (float) – max x coordinate of line
y0 (float) – min y coordinate of line
y1 (float) – max y coordinate of line
kwargs – keyword args

plot_xy(ir, ic, iline, df, x, y, leg_name, twin, zorder=1, line_type=None, marker_disable=False)¶

Plot xy data

Parameters

x (np.array) – x data to plot
y (np.array) – y data to plot
color (str) – hex color code for line color (default=’#000000’)
marker (str) – marker char string (default=’o’)
points (bool) – toggle points on|off (default=False)
line (bool) – toggle plot lines on|off (default=True)

Keyword Arguments

kwargs allowed by the plotter function selected (any) –

Returns

return the line plot object

save(filename)¶

see()¶: Prints a readable list of class attributes

set_axes_colors(ir, ic)¶

set_axes_grid_lines(ir, ic)¶

set_axes_labels(ir, ic)¶

set_axes_ranges(ir, ic)¶

set_axes_rc_labels(ir, ic)¶

set_axes_scale(ir, ic)¶

set_axes_ticks(ir, ic)¶

set_figure_title()¶

set_label_text(data, **kwargs)¶

Set the default label text

Parameters: data (Data object) – current Data object

show(inline=True)¶

update_from_data(data)¶: Make properties updates from the Data class

update_wrap(data, kwargs)¶: Update figure props based on wrap selections

class fivecentplots.engines.layout.DF_Element(label='None', fcpp={}, others={}, **kwargs)¶

property on¶

class fivecentplots.engines.layout.Element(label='None', fcpp={}, others={}, **kwargs)¶

color_alpha(attr, alpha)¶: Add alpha to each color in the color list and make it a RepeatedList

property kwargs¶

property on¶

see()¶: Prints a readable list of class attributes

property size¶

property size_inches¶

property text¶

class fivecentplots.engines.layout.Legend_Element(label='None', fcpp={}, others={}, **kwargs)¶

add_value(key, curve, line_type_name)¶

Add a new curve to the values dataframe

Parameters

key (str) – string name for legend label
curve (obj) – reference to curve obj
line_type_name (str) – line type description

del_value(key)¶

set_default()¶

property size¶

property values¶

fivecentplots.engines.layout.custom_formatwarning(msg, *args, **kwargs)¶

mpl.py¶

class fivecentplots.engines.mpl.Layout(plot_func, data, **kwargs)¶

add_box_labels(ir, ic, data)¶

add_box_points(ir, ic, x, y)¶: Plot x y points with or without jitter

add_cbar(ax, contour)¶: Add a color bar

add_hvlines(ir, ic, df=None)¶

Add axhlines and axvlines

Parameters

ir (int) – subplot row index
ic (int) – subplot col index
df (pd.DataFrame) – current data

add_label(ir, ic, text='', position=None, rotation=0, size=None, fill_color='#ffffff', edge_color='#aaaaaa', edge_width=1, font='sans-serif', font_weight='normal', font_style='normal', font_color='#666666', font_size=14, offset=False, **kwargs)¶

Add a label to the plot

This function can be used for title labels or for group labels applied to rows and columns when plotting facet grid style plots.

Parameters

label (str) – label text
pos (tuple) – label position tuple of form (left, right, top, bottom)
is (old) –
axis (matplotlib.axes) – mpl axes object
rotation (int) – degrees of rotation
fillcolor (str) – hex color code for label fill (default=’#ffffff’)
edgecolor (str) – hex color code for label edge (default=’#aaaaaa’)
color (str) – hex color code for label text (default=’#666666’)
weight (str) – label font weight (use standard mpl weights like ‘bold’)
fontsize (int) – label font size (default=14)

add_legend()¶

Add a figure legend: TODO: add separate_label support?

add_text(ir, ic, text=None, element=None, offsetx=0, offsety=0, **kwargs)¶: Add a text box

close()¶: Close existing plot windows

fill_between_lines(ir, ic, iline, x, lcl, ucl, obj, twin=False)¶

Shade a region between two curves

Args:

get_axes_label_position()¶

Get the position of the axes labels: self.label_@.position –> [left, right, top, bottom]

get_element_sizes(data)¶

Calculate the actual rendered size of select elements by pre-plotting them. This is needed to correctly adjust the figure dimensions

Parameters: data (obj) – data class object

get_figure_size(data, **kwargs)¶: Determine the size of the mpl figure canvas in pixels and inches

get_legend_position()¶: Get legend position

get_rc_label_position()¶

Get option group label positions: self.label.position –> [left, right, top, bottom]

get_subplots_adjust()¶

Calculate the subplots_adjust parameters for the axes: self.axes.position –> [left, right, top, bottom]

get_title_position()¶

Calculate the title position: self.title.position –> [left, right, top, bottom]

make_figure(data, **kwargs)¶: Make the figure and axes objects

plot_bar(ir, ic, iline, df, x, y, leg_name, data, stacked, std, ngroups=1)¶: Plot bar graph

plot_box(ir, ic, data, **kwargs)¶

Plot boxplot data

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
data (pd.DataFrame) – data to plot

Keyword Arguments

kwargs allowed by the plotter function selected (any) –

Returns

return the box plot object

plot_contour(ax, df, x, y, z, ranges)¶: Plot a contour plot

plot_heatmap(ax, df, x, y, z, ranges)¶

Plot a heatmap

Parameters

ax (mpl.axes) – current axes obj
df (pd.DataFrame) – data to plot
x (str) – x-column name
y (str) – y-column name
z (str) – z-column name
range (dict) – ax limits

plot_hist(ir, ic, iline, df, x, y, leg_name, data, zorder=1, line_type=None, marker_disable=False)¶

plot_line(ir, ic, x0, y0, x1=None, y1=None, **kwargs)¶

Plot a simple line

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
x0 (float) – min x coordinate of line
x1 (float) – max x coordinate of line
y0 (float) – min y coordinate of line
y1 (float) – max y coordinate of line
kwargs – keyword args

plot_polygon(ir, ic, points, **kwargs)¶

Plot a polygon

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
points (list of float) – points on the polygon
kwargs – keyword args

plot_xy(ir, ic, iline, df, x, y, leg_name, twin, zorder=1, line_type=None, marker_disable=False)¶

Plot xy data

Parameters

x (np.array) – x data to plot
y (np.array) – y data to plot
color (str) – hex color code for line color (default=’#000000’)
marker (str) – marker char string (default=’o’)
points (bool) – toggle points on|off (default=False)
line (bool) – toggle plot lines on|off (default=True)

Keyword Arguments

kwargs allowed by the plotter function selected (any) –

Returns

return the line plot object

save(filename, idx=0)¶

Save a plot window

Parameters: filename (str) – name of the file

see()¶: Prints a readable list of class attributes

set_axes_colors(ir, ic)¶

Set axes colors (fill, alpha, edge)

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

set_axes_grid_lines(ir, ic)¶

Style the grid lines and toggle visibility

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

set_axes_labels(ir, ic)¶

Set the axes labels

Parameters

ir (int) – current row index
ic (int) – current column index
kw (dict) – kwargs dict

set_axes_ranges(ir, ic, ranges)¶

Set the axes ranges

Parameters

ir (int) – subplot row index
ic (int) – subplot col index
limits (dict) – min/max axes limits for each axis

set_axes_ranges_hist(ir, ic, data, hist, iline)¶

Special range overrides for histogram plot: Needed to deal with the late computation of bin counts

Parameters

ir (int) – subplot row index
ic (int) – subplot col index
data (Data obj) – current data object
hist (mpl.hist obj) – result of hist plot

set_axes_rc_labels(ir, ic)¶

Add the row/column label boxes and wrap titles

Parameters

ir (int) – current row index
ic (int) – current column index

set_axes_scale(ir, ic)¶

Set the scale type of the axes

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

Returns

axes scale type

set_axes_ticks(ir, ic)¶

Configure the axes tick marks

Parameters

ax (mpl axes) – current axes to scale
kw (dict) – kwargs dict
y_only (bool) – flag to access on the y-axis ticks

set_colormap(data, **kwargs)¶

Replace the color list with discrete values from a colormap

Parameters: data (Data object) –

set_figure_title()¶: Add a figure title

set_scientific(ax, idx=0)¶

Turn off scientific notation

Parameters: ax – axis to adjust
Returns: updated axise

show(filename=None)¶: Handle display of the plot window

update_subplot_spacing()¶: Update spacing for long labels

fivecentplots.engines.mpl.custom_formatwarning(msg, *args, **kwargs)¶

fivecentplots.engines.mpl.iterticks(ax)¶

fivecentplots.engines.mpl.mpl_get_ticks(ax, xon=True, yon=True)¶

Divine a bunch of tick and label parameters for mpl layouts

Parameters: ax (mpl.axes) –
Returns: dict of x and y ax tick parameters

fivecentplots.engines.mpl.mplc_to_hex(color, alpha=True)¶

Convert mpl color to hex

Parameters

color (tuple) – matplotlib style color code
alpha (boolean) – include or exclude the alpha value

bokeh.py¶

class fivecentplots.engines.bokeh.Layout(plot_func, data, **kwargs)¶

add_box_labels(ir, ic, dd)¶

add_hvlines(ir, ic, df=None)¶

add_legend()¶: Add a figure legend

add_text(ir, ic, text=None, element=None, offsetx=0, offsety=0, **kwargs)¶: Add a text box

get_element_sizes(data)¶

get_figure_size(data, **kwargs)¶

make_figure(data, **kwargs)¶: Make the figure and axes objects

plot_box(ir, ic, data, **kwargs)¶

Plot boxplot data

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
data (pd.DataFrame) – data to plot

Keyword Arguments

kwargs allowed by the plotter function selected (any) –

Returns

return the box plot object

plot_contour(ax, df, x, y, z, ranges)¶: Plot a contour plot

plot_heatmap(ax, df, x, y, z, ranges)¶

Plot a heatmap

Parameters

ax (mpl.axes) – current axes obj
df (pd.DataFrame) – data to plot
x (str) – x-column name
y (str) – y-column name
z (str) – z-column name
range (dict) – ax limits

plot_hist(ir, ic, iline, df, x, y, leg_name, data, zorder=1, line_type=None, marker_disable=False)¶

plot_line(ir, ic, x0, y0, x1=None, y1=None, **kwargs)¶

Plot a simple line

Parameters

ir (int) – subplot row index
ic (int) – subplot column index
x0 (float) – min x coordinate of line
x1 (float) – max x coordinate of line
y0 (float) – min y coordinate of line
y1 (float) – max y coordinate of line
kwargs – keyword args

plot_xy(ir, ic, iline, df, x, y, leg_name, twin, zorder=1, line_type=None, marker_disable=False)¶

Plot xy data

Parameters

x (np.array) – x data to plot
y (np.array) – y data to plot
color (str) – hex color code for line color (default=’#000000’)
marker (str) – marker char string (default=’o’)
points (bool) – toggle points on|off (default=False)
line (bool) – toggle plot lines on|off (default=True)

Keyword Arguments

kwargs allowed by the plotter function selected (any) –

Returns

return the line plot object

save(filename, idx=0)¶

see()¶: Prints a readable list of class attributes

set_axes_colors(ir, ic)¶

Set axes colors (fill, alpha, edge)

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

set_axes_grid_lines(ir, ic)¶

Style the grid lines and toggle visibility

Parameters

ir (int) – subplot row index
ic (int) – subplot col index

set_axes_labels(ir, ic)¶

Set the axes labels

Parameters

ir (int) – current row index
ic (int) – current column index
kw (dict) – kwargs dict

set_axes_ranges(ir, ic, ranges)¶

Set the axes ranges

Parameters

ir (int) – subplot row index
ic (int) – subplot col index
limits (dict) – min/max axes limits for each axis

set_axes_rc_labels(ir, ic)¶

set_axes_scale(ir, ic)¶

set_axes_scale2(ir, ic)¶: This appears to need to happen at instantiation of the figure

set_axes_ticks(ir, ic)¶

set_figure_title()¶: Add a figure title

show(filename=None)¶: Handle display of the plot window

fivecentplots.engines.bokeh.custom_formatwarning(msg, *args, **kwargs)¶

fivecentplots.engines.bokeh.fill_alpha(hexstr)¶: Break an 8-digit hex string into a hex color and a fractional alpha value

fivecentplots.engines.bokeh.format_marker(fig, marker)¶: Format the marker string to mathtext

utilities.py¶

exception fivecentplots.utilities.PlatformError¶

class fivecentplots.utilities.RepeatedList(values, name)¶

get(idx)¶

fivecentplots.utilities.ci(data, coeff=0.95)¶

Compute the confidence interval

Parameters: data (pd.Series) – raw data for computation
Returns: lower confidence interval, upper confidence interval returns np.nan if standard err < 0

fivecentplots.utilities.df_filter(df, filt_orig, drop_cols=False)¶

Filter the DataFrame

Due to limitations in pd.query, column names must not have spaces. This function will temporarily replace spaces in the column names with underscores, but the supplied query string must contain column names without any spaces

Parameters

df (pd.DataFrame) – DataFrame to filter
filt_orig (str) – query expression for filtering
drop_cols (bool) – drop filtered columns from results

Returns

filtered DataFrame

fivecentplots.utilities.df_summary(df, columns=[], exclude=[], multiple=False)¶

Return a summary table of unique conditions in a DataFrame

If more than one value exists, replace with “Multiple” or a string list of the values

Parameters

df (pd.DataFrame) – input DataFrame
columns (list) – list of column names to include; if empty, include all columns
exclude (list) – list of column names to ignore
multiple (bool) – toggle between showing discrete values or “Multiple” when a column contains more than one value

fivecentplots.utilities.df_unique(df)¶

Get column names with one unique value

Parameters: df (pd.DataFrame) – data to check
Returns: dict of col names and unique values

fivecentplots.utilities.dfkwarg(args, kwargs)¶

Add the DataFrame to kwargs

Parameters

args (tuple) – *args sent to plot
kwargs (dict) – **kwargs sent to plot

Returns

updated kwargs

fivecentplots.utilities.get_current_values(df, text, key='@')¶

Parse a string looking for text enclosed by ‘key’ and replace with the current value from the DataFrame

Parameters

df (pd.DataFrame) – DataFrame containing values we are looking for
text (str) – string to parse
key (str) – matching chars that enclose the value to replace from df

Returns

updated string

fivecentplots.utilities.get_decimals(value, max_places=4)¶

Get the number of decimal places of a float number excluding rounding errors

Parameters

value (int|float) – value to check
max_places (int) – maximum number of decimal places to check

Returns

number of decimal places

fivecentplots.utilities.get_mpl_version_dir()¶: Get the matplotlib version directory for test images based on the current version of mpl

fivecentplots.utilities.get_text_dimensions(text, **kwargs)¶

fivecentplots.utilities.img_compare(img1, img2, show=False)¶

Read two images and compare for difference by pixel This is an optional utility used only for developer tests, so the function will only work if opencv is installed :param img1: path to file #1 :type img1: str :param img2: path to file #2 :type img2: str :param show: display the difference :type show: bool

Returns: True/False of existence of differences

fivecentplots.utilities.kwget(dict1, dict2, val, default)¶

Augmented kwargs.get function

Parameters

dict1 (dict) – first dictionary to check for the value
dict2 (dict) – second dictionary to check for the value
val (str) – value to look for
default (multiple) – default value if not found in dict1 or dict2 keys

Returns

value to use

fivecentplots.utilities.nq(data, column='Value', **kwargs)¶: Normal quantile calculation

fivecentplots.utilities.plot_num(ir, ic, ncol)¶: Get the plot number based on grid location

fivecentplots.utilities.rectangle_overlap(r1, r2)¶

Determine if the bounds of two rectangles overlap

Parameters

r1 (list|tuple) – width, height, center point (x, y) of left rectangle
r2 (list|tuple) – width, height, center point (x, y) of right rectangle

Returns

True if overlap | False if not

fivecentplots.utilities.reload_defaults(theme=None)¶: Reload the fcp params

fivecentplots.utilities.set_save_filename(df, ifig, fig_item, fig_cols, layout, kwargs)¶

Build a filename based on the plot setup parameters

Parameters

df (pd.DataFrame) – input data used for the plot
fig_item (None | str) – unique figure item
fig_cols (None | str | list) – names of columns used to generate fi
layout (obj) – plot layout object
kwargs (dict) – input keyword args

Returns

str filename

fivecentplots.utilities.sigma(x)¶

Calculate the sigma range for a data set

Parameters: x (pd.Series | np.array) – data set
Returns: int value to use for +/- max sigma

fivecentplots.utilities.validate_list(items)¶

Make sure a list variable is actually a list and not a single string

Parameters: items (str|list) – values to check dtype
Returns: items as a list