Histogram Plot¶

plot_hist(tables, variables, dt1, dt2, lat1, lat2, lon1, lon2, depth1, depth2, exportDataFlag=False, show=True)¶

Creates a histogram graph for each variable according to the specified space-time constraints (dt1, dt2, lat1, lat2, lon1, lon2, depth1, depth2). Change the APIs vizEngine parameter if you wish to use a different visualization library. Returns the generated graph objects in form of a python list. One may use the returned objects to modify the graph properties.

Note

This method requires a valid API key. It is not necessary to set the API key every time because the API properties are stored locally after being called the first time.

Parameters:

tables: list of string: Table names (each dataset is stored in a table). A full list of table names can be found in Data Catalog.
variable: list of string: Variable short name which directly corresponds to a field name in the table. A full list of variable short names can be found in Data Catalog.
dt1: string: Start date or datetime. This parameter sets the lower bound of the temporal cut. Example values: ‘2016-05-25’ or ‘2017-12-10 17:25:00’
dt2: string: End date or datetime. This parameter sets the upper bound of the temporal cut. Example values: ‘2016-05-25’ or ‘2017-12-10 17:25:00’
lat1: float: Start latitude [degree N]. This parameter sets the lower bound of the meridional cut. Note latitude ranges from -90° to 90°.
lat2: float: End latitude [degree N]. This parameter sets the upper bound of the meridional cut. Note latitude ranges from -90° to 90°.
lon1: float: Start longitude [degree E]. This parameter sets the lower bound of the zonal cut. Note longitude ranges from -180° to 180°.
lon2: float: End longitude [degree E]. This parameter sets the upper bound of the zonal cut. Note longitude ranges from -180° to 180°.
depth1: float: Start depth [m]. This parameter sets the lower bound of the vertical cut. Note depth is a positive number (it is 0 at the surface and increases towards the ocean floor).
depth2: float: End depth [m]. This parameter sets the upper bound of the vertical cut. Note depth is a positive number (it is 0 at the surface and increases towards the ocean floor).
exportDataFlag: boolean, default: False: If True, the graph data points are stored on the local machine. The export path and file format are set by the APIs parameters.
show: boolean, default: True: If True, the graph object is returned and is displayed. The graph file is saved on the local machine at the figureDir directory. If False, the graph object is returned but not displayed.

Returns:

A list of graph objects. Below are the graph’s properties and methods.

Properties:

data: dataframe: Graph data points to be visualized.
bins: int, default: 50: Number of histogram bins.
pdf: boolean, default: False: If True the histogram shows a probability density function, otherwise absolute counts are displayed.
height: int: Graph’s height in pixels.
width: int: Graph’s width in pixels.
xlabel: str: Graph’s x-axis label.
ylabel: str: Graphs’s y-axis label.
title: str: Graphs’s title.

Methods:

render(): Displays the plot according to the set properties.

Example 1:

This example creates three histogram graphs comparing dissolved oxygen measured during the Falkor_2018 cruise, estimated by Darwin climatology model, and World Ocean Atlas. The graphs are made using the default visualization library (plotly) which may be changed by: pycmap.API(vizEngine='bokeh')

#!pip install pycmap -q     #uncomment to install pycmap, if necessary
# uncomment the lines below if the API key has not been registered on your machine, previously.
# import pycmap
# pycmap.API(token='YOUR_API_KEY>')


from pycmap.viz import plot_hist

go = plot_hist(
              tables=['tblFalkor_2018', 'tblDarwin_Nutrient_Climatology', 'tblWOA_Climatology'],
              variables=['CTD_Oxygen', 'O2_darwin_clim', 'oxygen_WOA_clim'],
              dt1='2018-03-01',
              dt2='2018-04-30',
              lat1=21,
              lat2=25,
              lon1=-161,
              lon2=155,
              depth1=0,
              depth2=100,
              exportDataFlag=False,
              show=True
              )

# here is how to modify a graph:

go[0].bins = 20
go[0].pdf = False
go[0].height = 600
go[0].width = 600
go[0].xlabel = "new xlabel"
go[0].title= "graph's title"
go[0].render()