CovidChart Class#

class CovidChart.CovidChart#

Bases: object

This class is used to create charts using COVID-19 data. All formatting is carried out by this class with lines of best fit added for scatter graphs. To change graph formatting amend the method draw_chart()

add_bar_chart(x_data, y_data, colour, label='', display_vals=True, to_bar_over=True)#

Use when creating just bar charts without a line of best fit and totals at the top of each bar

Args:

x_data: List or DataFrame, data for the x-axis of your bar plot
y_data: List or DataFrame, data for the y-axis of your bar plot
colour: String Value, color of the plot, can be a word such as “red” or a hex value
label: String Value optional, This is the label used for the legend, to_bar_over must be set to False for the legend to be displayed
display_vals: Boolean Value optional, set to true to display numbers above the bars
to_bar_over: Boolean Value optional, set to true if you don’t want a legend, set to false for a legend

add_bar_plot(x_data, y_data, colour, label)#

Adds a bar plot with line of best fit to a plot, this just adds the data once draw_chart is called the plot will be saved and/or displayed on screen

Args:

x_data: List or DataFrame, data for the x-axis of your bar plot
y_data: List or DataFrame, data for the y-axis of your bar plot
colour: String Value, color of the plot, can be a word such as “red” or a hex value
label: String Value, The label for the plot, this will be used in the legend

add_scatter_plot(x_data, y_data, colour, label, to_dash, data_complete, to_clip=False, tolerance=1.2)#

Adds a scatter plot with line of best fit to a plot, this just adds the data once draw_chart is called the plot will be saved and/or displayed on screen

Args:

x_data: List or DataFrame, data for the x-axis of your scatter chart
y_data: List or DataFrame, data for the y-axis of your chart
colour: String Value, color of the plot, can be a word such as “red” or a hex value
label: String Value, The label for the plot, this will be used in the legend
to_dash: Boolean Value, decides if the plot should have a solid or dashed line of best fit
data_complete: Boolean value, if set to true the LOBF will go to the end, if set to False the LOBF will go to (values - (time/2)), set to False if data is incomplete
to_clip: Boolean Value, if this is true any plot that is greater than the (averaged value * tolerance) then the plot value will be changed to the average value, this allows us to clip data points that are alot higher than the averaged value.
tolerance: Float Value, the tolerance for clipping, set to 1.2 by default which is 20%.

add_treemap(data, labels, colours)#

Creates a treeMap diagram with data (list) and labels (list) The data should already be summed when calling this method therefore data should be an list of summed data

Args:

data: List or DataFrame, data for the treemap. This data should not be timeseries, see the example in example.py
labels: List or DataFrame, The label for the plot, this will be used in the legend
colours: List or DataFrame, color of the plot, can be a word such as “red” or a hex value

clear_chart()#

Clears the chart saving the original params

..Note:: This should be called before creating another chart

create_time_stamp(img_path, x_pos, y_pos, fontsize, to_be_wide, hos_data=False)#

Adds a timestamp to the chart with the website URL

Args:

img_path: String Value, image path of where the chart is saved
x_pos: Integer Value, start position of the timestamp for the x-axis
y_pos: Integer Value, start position of the timestamp for the y-axis
fontsize: Integer Value, size of the fonts to be used
to_be_wide: Boolean value, is the charts aspect ratio wide or portait - decides if the stamp is to go at the top or bottom of the chart

Note

image_path is the path to the image including the file name extension, this will be .png for charts created by this class

draw_Scatter_Year_Comp(data, to_show, label, to_be_wide, y_dates, to_stamp)#

Give this method some data and it will split it into years and plot a year comparison with daily averages

Args:

data: List, data be to plotted on the y-axis
to_show: Boolean Value, deicdes if the chart should be shown
label: String Value, sets the label for the plots also used in the file name and title
to_be_wide: Boolean Value, sets aspect ratio to either landscape or portrait
y_dates: List, list of dates for the y-axis by default I used data/static/dates.csv, this will give you comparison charts starting and ending at March of each year
to_stamp: Boolean Value, decides if a time stamp should be added to the chart

draw_chart(x_axis_title, y_axis_title, title, file_name, to_be_wide, hos_data=False)#

Draws the chart either on screen if to_show == true (set_chart_params) or as a png image saved with the file_name variable These graphs use ONS guidelines for formatting

Args:

x_axis_title: String Value, Title for the x-axis
y_axis_title: String Value, Title for the y-axis
title: String Value, Title for the chart
file_name: String Value, file name of the chart (DO NOT INCLUDE FILE EXTENSION; this is added by this method)
to_be_wide: Boolean value, decides the aspect ratio of the chart, wide or portrait

Note

Do not add the file extension for the file name argument, this extension will always be .png and is added by this method

draw_v_lines()#: Draws vertical lines on charts indicating key moments. If any key moments need to be added add them in this method get_gov_date_Series() or govAgedDateSeries() should be used with this method and not dataframe[“date”] as this will give an error

reset_max_y_value()#: Resets ylimit if it was explicitly set

set_LOBF_time(time)#

Changes the averaged time in days for LOBF set my the argument time

Args:

time: This is the amount of time in days for averaging the data

set_chart_params(to_show, show_leg, to_add, to_stamp)#

Use to change the parameters of the COVID chart i.e. to show the chart, to add a time stamp, etc

Args:

to_show: Boolean Value, decides whether to show the plot in python
show_leg: Boolean Value, decides if the default COVID legend should be displayed with VLINES. You might want to show the VLINES without the legend
to_add: Boolean Value, Boolean Value, decides if the VLINES should be added to the chart
to_stamp: Boolean Value, decides if the time stamp should be added to the chart

..Note:

set_legend_bottom(value)#

Use this if you wnat to change the position of the legend

Args:

value: Boolean Value, if set to True the legend will be at the bottom of the chart otherwise it will be at the top left of the chart

set_legend_cols(value)#

Use this to change how many columns we have in the legend

Args:

value: Integer Value, this will be the number of columns in the legend when its at the botton of the chart

set_max_y_value(value)#

sets the maximum Y valve

Args:

value: Integer Value, sets the maxmum value for the Y-axis

set_start_date(start_date)#

Sets the start date for the graph to be used if you want to show VLINES when starting from a different date to the default one

Args:

start_date: Date Value, used to set a different start date when to_add == True (set_chart_params). By default the start date is 20nd March 2020. This can be changed if required

ReadVaxData Class

CovidDashboard Class