updating plot line with different number of columns

Hi,

I have dataframe

s4= {‘females’: {‘2012’: 76.9, ‘2007’: 75.9, ‘2005’: 75.9, ‘2014’: 77.5, ‘2004’: 75.8, ‘2000’: 75.2, ‘2013’: 77.5, ‘2006’: 76.2, ‘2002’: 75.6, ‘2008’: 76.5, ‘2010’: 77.2, ‘2001’: 76.1, ‘2011’: 77.2, ‘2003’: 75.7, ‘2009’: 76.7, ‘2015’: 77.4, ‘2016’: 77.5}, ‘males’: {‘2012’: 73.0, ‘2007’: 71.8, ‘2005’: 71.6, ‘2014’: 73.5, ‘2004’: 71.5, ‘2000’: 70.8, ‘2013’: 73.4, ‘2006’: 71.7, ‘2002’: 70.6, ‘2008’: 72.4, ‘2010’: 72.9, ‘2001’: 70.9, ‘2011’: 73.1, ‘2003’: 70.9, ‘2009’: 72.3, ‘2015’: 73.5, ‘2016’: 73.4}, ‘total’: {‘2012’: 74.9, ‘2007’: 73.8, ‘2005’: 73.7, ‘2014’: 75.5, ‘2004’: 73.6, ‘2000’: 73.0, ‘2013’: 75.5, ‘2006’: 73.9, ‘2002’: 73.0, ‘2008’: 74.4, ‘2010’: 75.0, ‘2001’: 73.4, ‘2011’: 75.1, ‘2003’: 73.2, ‘2009’: 74.4, ‘2015’: 75.5, ‘2016’: 75.4}}

with following columns: Years, females, males and total

.

When updating on click button event I get new dataframe

s4= {‘value’: {Timestamp(‘2017-01-01 00:00:00’): nan, Timestamp(‘2015-01-01 00:00:00’): 41.6, Timestamp(‘2001-01-01 00:00:00’): nan, Timestamp(‘2002-01-01 00:00:00’): nan, Timestamp(‘2011-01-01 00:00:00’): 50.4, Timestamp(‘2004-01-01 00:00:00’): nan, Timestamp(‘2014-01-01 00:00:00’): 43.3, Timestamp(‘2005-01-01 00:00:00’): nan, Timestamp(‘2009-01-01 00:00:00’): nan, Timestamp(‘2010-01-01 00:00:00’): 47.2, Timestamp(‘2007-01-01 00:00:00’): nan, Timestamp(‘2016-01-01 00:00:00’): 41.1, Timestamp(‘2008-01-01 00:00:00’): nan, Timestamp(‘2003-01-01 00:00:00’): nan, Timestamp(‘2013-01-01 00:00:00’): 48.1, Timestamp(‘2000-01-01 00:00:00’): nan, Timestamp(‘2012-01-01 00:00:00’): 50.3, Timestamp(‘2006-01-01 00:00:00’): nan}}

with following columns: Years, value.

The question is how to show in first time plot with 3 lines (from dataframe df1) and appropriate legend and after updating to show in the same figure plot with one line (dataframe df2) and appropriate legend.

I tried to define one column data source with same structure (columns: Year, Value, var1, var2, var3, var4 ) but I have a problem to showin the plot figure because in both cases plot shows aditional line with values 0. (see im1 and im 2 in attachment) For im1 columndatasource looks like {‘var4’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘Value’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘var1’: [75.2, 76.1, 75.6, 75.7, 75.8, 75.9, 76.2, 75.9, 76.5, 76.7, 77.2, 77.2, 76.9, 77.5, 77.5, 77.4, 77.5], ‘var2’: [70.8, 70.9, 70.6, 70.9, 71.5, 71.6, 71.7, 71.8, 72.4, 72.3, 72.9, 73.1, 73.0, 73.4, 73.5, 73.5, 73.4], ‘Year’: [‘2000’, ‘2001’, ‘2002’, ‘2003’, ‘2004’, ‘2005’, ‘2006’, ‘2007’, ‘2008’, ‘2009’, ‘2010’, ‘2011’, ‘2012’, ‘2013’, ‘2014’, ‘2015’, ‘2016’], ‘var3’: [73.0, 73.4, 73.0, 73.2, 73.6, 73.7, 73.9, 73.8, 74.4, 74.4, 75.0, 75.1, 74.9, 75.5, 75.5, 75.5, 75.4]} and for im2 Column data source looks like {‘Value’: [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 47.2, 50.4, 50.3, 48.1, 43.3, 41.6, 41.1, nan], ‘var4’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘Year’: [Timestamp(‘2000-01-01 00:00:00’), Timestamp(‘2001-01-01 00:00:00’), Timestamp(‘2002-01-01 00:00:00’), Timestamp(‘2003-01-01 00:00:00’), Timestamp(‘2004-01-01 00:00:00’), Timestamp(‘2005-01-01 00:00:00’), Timestamp(‘2006-01-01 00:00:00’), Timestamp(‘2007-01-01 00:00:00’), Timestamp(‘2008-01-01 00:00:00’), Timestamp(‘2009-01-01 00:00:00’), Timestamp(‘2010-01-01 00:00:00’), Timestamp(‘2011-01-01 00:00:00’), Timestamp(‘2012-01-01 00:00:00’), Timestamp(‘2013-01-01 00:00:00’), Timestamp(‘2014-01-01 00:00:00’), Timestamp(‘2015-01-01 00:00:00’), Timestamp(‘2016-01-01 00:00:00’), Timestamp(‘2017-01-01 00:00:00’)], ‘var1’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘var3’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘var2’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}

Below is part of the code I use for generating plot line with appropriate legend.

Please help

Thanks,

Goran

s4= {‘females’: {‘2012’: 76.9, ‘2007’: 75.9, ‘2005’: 75.9, ‘2014’: 77.5, ‘2004’: 75.8, ‘2000’: 75.2, ‘2013’: 77.5, ‘2006’: 76.2, ‘2002’: 75.6, ‘2008’: 76.5, ‘2010’: 77.2, ‘2001’: 76.1, ‘2011’: 77.2, ‘2003’: 75.7, ‘2009’: 76.7, ‘2015’: 77.4, ‘2016’: 77.5}, ‘males’: {‘2012’: 73.0, ‘2007’: 71.8, ‘2005’: 71.6, ‘2014’: 73.5, ‘2004’: 71.5, ‘2000’: 70.8, ‘2013’: 73.4, ‘2006’: 71.7, ‘2002’: 70.6, ‘2008’: 72.4, ‘2010’: 72.9, ‘2001’: 70.9, ‘2011’: 73.1, ‘2003’: 70.9, ‘2009’: 72.3, ‘2015’: 73.5, ‘2016’: 73.4}, ‘total’: {‘2012’: 74.9, ‘2007’: 73.8, ‘2005’: 73.7, ‘2014’: 75.5, ‘2004’: 73.6, ‘2000’: 73.0, ‘2013’: 75.5, ‘2006’: 73.9, ‘2002’: 73.0, ‘2008’: 74.4, ‘2010’: 75.0, ‘2001’: 73.4, ‘2011’: 75.1, ‘2003’: 73.2, ‘2009’: 74.4, ‘2015’: 75.5, ‘2016’: 75.4}}

if len(list(s4.columns)) == 1:

source = ColumnDataSource(data=dict(Year=list(s4.index),

Value=list(s4[list(s4.columns)[0]]),

var1=[0]*len(list(s4.index)),

var2=[0]*len(list(s4.index)),

var3=[0]*len(list(s4.index)),

var4=[0]*len(list(s4.index))))

elif len(list(s4.columns)) == 2:

source = ColumnDataSource(data=dict(Year=list(s4.index),

Value=[0]*len(list(s4.index)),

var1=list(s4[list(s4.columns)[0]]),

var2=list(s4[list(s4.columns)[1]]),

var3=[0]*len(list(s4.index)),

var4=[0]*len(list(s4.index))))

elif len(list(s4.columns)) == 3:

source = ColumnDataSource(data=dict(Year=list(s4.index),

Value=[0]*len(list(s4.index)),

var1=list(s4[list(s4.columns)[0]]),

var2=list(s4[list(s4.columns)[1]]),

var3=list(s4[list(s4.columns)[2]]),

var4=[0]*len(list(s4.index))))

elif len(list(s4.columns)) == 4:

source = ColumnDataSource(data=dict(Year=list(s4.index),

Value=[0]*len(list(s4.index)),

var1=list(s4[list(s4.columns)[0]]),

var2=list(s4[list(s4.columns)[1]]),

var3=list(s4[list(s4.columns)[2]]),

var4=list(s4[list(s4.columns)[3]])))

def make_plotLine(source, title, subtitle, yunits):

cols = list(s4.columns)

b= [‘0’]*(4 - len(cols))

cols.extend(b)

if list(s4.columns) == 1:

b= [‘0’]*(4 - len(cols))

cols.extend(b)

elif list(s4.columns) == 2:

cols.insert(0, “0”)

b= [‘0’]*(4 - len(cols))

cols.extend(b)

elif list(s4.columns) == 3:

cols.insert(0, “0”)

b= [‘0’]*(4 - len(cols))

cols.extend(b)

elif list(s4.columns) == 4:

cols.insert(0, “0”)

b= [‘0’]*(4 - len(cols))

cols.extend(b)

color = [‘red’, ‘blue’, ‘green’, ‘orange’]

colors = color[:len(s4.columns)]

p2 = figure(x_axis_type=“datetime”, title=title, plot_width=800, plot_height=500)

p21 = p2.line(x=‘Year’, y=‘Value’, source=source, line_width=4, alpha=0.5, color=color[0])

p22 = p2.line(x=‘Year’, y=‘var1’, source=source, line_width=4, alpha=0.5, color=color[0])

p23 = p2.line(x=‘Year’, y=‘var2’, source=source, line_width=4, alpha=0.5, color=color[1])

p24 = p2.line(x=‘Year’, y=‘var3’, source=source, line_width=4, alpha=0.5, color=color[2])

p25 = p2.line(x=‘Year’, y=‘var4’, source=source, line_width=4, alpha=0.5, color=color[3])

if list(s4.columns) == 1:

p21.visible = True

p22.visible = False

p23.visible = False

p24.visible = False

p25.visible = False

elif list(s4.columns) == 2:

p21.visible = False

p22.visible = True

p23.visible = True

p24.visible = False

p25.visible = False

elif list(s4.columns) == 3:

p21.visible = False

p22.visible = True

p23.visible = True

p24.visible = True

p25.visible = False

elif list(s4.columns) == 4:

p21.visible = False

p22.visible = True

p23.visible = True

p24.visible = True

p25.visible = True

p2.xaxis.axis_label = None

p2.yaxis.axis_label = yunits

p2.x_range = DataRange1d(range_padding=0.1)

p2.grid.grid_line_alpha = 0.3

p2.xaxis.formatter=DatetimeTickFormatter(

years=["%Y"]

)

p2.min_border_bottom = 0

p2.yaxis.minor_tick_line_color = None

p2.legend.location = “bottom_right”

legend = Legend(items=[

(cols[0] , [p22]),

(cols[1] , [p23]),

(cols[2] , [p24]),

(cols[3] , [p25]),

], location=(200, -10))

p2.add_layout(legend, ‘below’)

p2.lod_timeout

p2.legend.click_policy=“hide”

p2.legend.orientation = “horizontal”

p2.title.text_font_size = ‘11pt’

return p2

def rr(attributes):

def python_callback(event):

source.data.update(source1.data)

plot_line = make_plotLine(source, title, subtitle, yunits)

plot_line.title.text = title

plot_bar.title.text = titlebar

Hi,

You are already adding a Legend and configuring its items manually, you will have to clear out Legend.items of the existing legend that you added, and re-configure .items with the new contents you want to see.

Thanks,

Bryan

···

On Mar 7, 2019, at 12:31 PM, Goran Goki <[email protected]> wrote:

Hi,

I have dataframe

s4= {'females': {'2012': 76.9, '2007': 75.9, '2005': 75.9, '2014': 77.5, '2004': 75.8, '2000': 75.2, '2013': 77.5, '2006': 76.2, '2002': 75.6, '2008': 76.5, '2010': 77.2, '2001': 76.1, '2011': 77.2, '2003': 75.7, '2009': 76.7, '2015': 77.4, '2016': 77.5}, 'males': {'2012': 73.0, '2007': 71.8, '2005': 71.6, '2014': 73.5, '2004': 71.5, '2000': 70.8, '2013': 73.4, '2006': 71.7, '2002': 70.6, '2008': 72.4, '2010': 72.9, '2001': 70.9, '2011': 73.1, '2003': 70.9, '2009': 72.3, '2015': 73.5, '2016': 73.4}, 'total': {'2012': 74.9, '2007': 73.8, '2005': 73.7, '2014': 75.5, '2004': 73.6, '2000': 73.0, '2013': 75.5, '2006': 73.9, '2002': 73.0, '2008': 74.4, '2010': 75.0, '2001': 73.4, '2011': 75.1, '2003': 73.2, '2009': 74.4, '2015': 75.5, '2016': 75.4}}

with following columns: Years, females, males and total
.
When updating on click button event I get new dataframe
s4= {'value': {Timestamp('2017-01-01 00:00:00'): nan, Timestamp('2015-01-01 00:00:00'): 41.6, Timestamp('2001-01-01 00:00:00'): nan, Timestamp('2002-01-01 00:00:00'): nan, Timestamp('2011-01-01 00:00:00'): 50.4, Timestamp('2004-01-01 00:00:00'): nan, Timestamp('2014-01-01 00:00:00'): 43.3, Timestamp('2005-01-01 00:00:00'): nan, Timestamp('2009-01-01 00:00:00'): nan, Timestamp('2010-01-01 00:00:00'): 47.2, Timestamp('2007-01-01 00:00:00'): nan, Timestamp('2016-01-01 00:00:00'): 41.1, Timestamp('2008-01-01 00:00:00'): nan, Timestamp('2003-01-01 00:00:00'): nan, Timestamp('2013-01-01 00:00:00'): 48.1, Timestamp('2000-01-01 00:00:00'): nan, Timestamp('2012-01-01 00:00:00'): 50.3, Timestamp('2006-01-01 00:00:00'): nan}}

with following columns: Years, value.

The question is how to show in first time plot with 3 lines (from dataframe df1) and appropriate legend and after updating to show in the same figure plot with one line (dataframe df2) and appropriate legend.
I tried to define one column data source with same structure (columns: Year, Value, var1, var2, var3, var4 ) but I have a problem to showin the plot figure because in both cases plot shows aditional line with values 0. (see im1 and im 2 in attachment) For im1 columndatasource looks like {'var4': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'Value': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'var1': [75.2, 76.1, 75.6, 75.7, 75.8, 75.9, 76.2, 75.9, 76.5, 76.7, 77.2, 77.2, 76.9, 77.5, 77.5, 77.4, 77.5], 'var2': [70.8, 70.9, 70.6, 70.9, 71.5, 71.6, 71.7, 71.8, 72.4, 72.3, 72.9, 73.1, 73.0, 73.4, 73.5, 73.5, 73.4], 'Year': ['2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016'], 'var3': [73.0, 73.4, 73.0, 73.2, 73.6, 73.7, 73.9, 73.8, 74.4, 74.4, 75.0, 75.1, 74.9, 75.5, 75.5, 75.5, 75.4]} and for im2 Column data source looks like {'Value': [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 47.2, 50.4, 50.3, 48.1, 43.3, 41.6, 41.1, nan], 'var4': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'Year': [Timestamp('2000-01-01 00:00:00'), Timestamp('2001-01-01 00:00:00'), Timestamp('2002-01-01 00:00:00'), Timestamp('2003-01-01 00:00:00'), Timestamp('2004-01-01 00:00:00'), Timestamp('2005-01-01 00:00:00'), Timestamp('2006-01-01 00:00:00'), Timestamp('2007-01-01 00:00:00'), Timestamp('2008-01-01 00:00:00'), Timestamp('2009-01-01 00:00:00'), Timestamp('2010-01-01 00:00:00'), Timestamp('2011-01-01 00:00:00'), Timestamp('2012-01-01 00:00:00'), Timestamp('2013-01-01 00:00:00'), Timestamp('2014-01-01 00:00:00'), Timestamp('2015-01-01 00:00:00'), Timestamp('2016-01-01 00:00:00'), Timestamp('2017-01-01 00:00:00')], 'var1': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'var3': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'var2': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}

Below is part of the code I use for generating plot line with appropriate legend.
Please help
Thanks,
Goran

s4= {'females': {'2012': 76.9, '2007': 75.9, '2005': 75.9, '2014': 77.5, '2004': 75.8, '2000': 75.2, '2013': 77.5, '2006': 76.2, '2002': 75.6, '2008': 76.5, '2010': 77.2, '2001': 76.1, '2011': 77.2, '2003': 75.7, '2009': 76.7, '2015': 77.4, '2016': 77.5}, 'males': {'2012': 73.0, '2007': 71.8, '2005': 71.6, '2014': 73.5, '2004': 71.5, '2000': 70.8, '2013': 73.4, '2006': 71.7, '2002': 70.6, '2008': 72.4, '2010': 72.9, '2001': 70.9, '2011': 73.1, '2003': 70.9, '2009': 72.3, '2015': 73.5, '2016': 73.4}, 'total': {'2012': 74.9, '2007': 73.8, '2005': 73.7, '2014': 75.5, '2004': 73.6, '2000': 73.0, '2013': 75.5, '2006': 73.9, '2002': 73.0, '2008': 74.4, '2010': 75.0, '2001': 73.4, '2011': 75.1, '2003': 73.2, '2009': 74.4, '2015': 75.5, '2016': 75.4}}

if len(list(s4.columns)) == 1:
        source = ColumnDataSource(data=dict(Year=list(s4.index),
                                            Value=list(s4[list(s4.columns)[0]]),
                                            var1=[0]*len(list(s4.index)),
                                            var2=[0]*len(list(s4.index)),
                                            var3=[0]*len(list(s4.index)),
                                            var4=[0]*len(list(s4.index))))
        
    elif len(list(s4.columns)) == 2:
        source = ColumnDataSource(data=dict(Year=list(s4.index),
                                            Value=[0]*len(list(s4.index)),
                                            var1=list(s4[list(s4.columns)[0]]),
                                            var2=list(s4[list(s4.columns)[1]]),
                                            var3=[0]*len(list(s4.index)),
                                            var4=[0]*len(list(s4.index))))
    elif len(list(s4.columns)) == 3:
        source = ColumnDataSource(data=dict(Year=list(s4.index),
                                            Value=[0]*len(list(s4.index)),
                                            var1=list(s4[list(s4.columns)[0]]),
                                            var2=list(s4[list(s4.columns)[1]]),
                                            var3=list(s4[list(s4.columns)[2]]),
                                            var4=[0]*len(list(s4.index))))
    elif len(list(s4.columns)) == 4:
        source = ColumnDataSource(data=dict(Year=list(s4.index),
                                            Value=[0]*len(list(s4.index)),
                                            var1=list(s4[list(s4.columns)[0]]),
                                            var2=list(s4[list(s4.columns)[1]]),
                                            var3=list(s4[list(s4.columns)[2]]),
                                            var4=list(s4[list(s4.columns)[3]])))

def make_plotLine(source, title, subtitle, yunits):
    cols = list(s4.columns)
    b= ['0']*(4 - len(cols))
    cols.extend(b)

    if list(s4.columns) == 1:
        b= ['0']*(4 - len(cols))
        cols.extend(b)
    elif list(s4.columns) == 2:
        cols.insert(0, "0")
        b= ['0']*(4 - len(cols))
        cols.extend(b)

    elif list(s4.columns) == 3:
        cols.insert(0, "0")
        b= ['0']*(4 - len(cols))
        cols.extend(b)

    elif list(s4.columns) == 4:
        cols.insert(0, "0")
        b= ['0']*(4 - len(cols))
        cols.extend(b)
        
    color = ['red', 'blue', 'green', 'orange']
    colors = color[:len(s4.columns)]
    
    p2 = figure(x_axis_type="datetime", title=title, plot_width=800, plot_height=500)

    p21 = p2.line(x='Year', y='Value', source=source, line_width=4, alpha=0.5, color=color[0])
    p22 = p2.line(x='Year', y='var1', source=source, line_width=4, alpha=0.5, color=color[0])
    p23 = p2.line(x='Year', y='var2', source=source, line_width=4, alpha=0.5, color=color[1])
    p24 = p2.line(x='Year', y='var3', source=source, line_width=4, alpha=0.5, color=color[2])
    p25 = p2.line(x='Year', y='var4', source=source, line_width=4, alpha=0.5, color=color[3])

    if list(s4.columns) == 1:
        p21.visible = True
        p22.visible = False
        p23.visible = False
        p24.visible = False
        p25.visible = False

    elif list(s4.columns) == 2:
        p21.visible = False
        p22.visible = True
        p23.visible = True
        p24.visible = False
        p25.visible = False

    elif list(s4.columns) == 3:
        p21.visible = False
        p22.visible = True
        p23.visible = True
        p24.visible = True
        p25.visible = False

    elif list(s4.columns) == 4:
        p21.visible = False
        p22.visible = True
        p23.visible = True
        p24.visible = True
        p25.visible = True
        
    p2.xaxis.axis_label = None
    p2.yaxis.axis_label = yunits
    p2.x_range = DataRange1d(range_padding=0.1)
    p2.grid.grid_line_alpha = 0.3
    p2.xaxis.formatter=DatetimeTickFormatter(
        years=["%Y"]
        )
    p2.min_border_bottom = 0
    p2.yaxis.minor_tick_line_color = None
    
    p2.legend.location = "bottom_right"

    legend = Legend(items=[
        (cols[0] , [p22]),
        (cols[1] , [p23]),
        (cols[2] , [p24]),
        (cols[3] , [p25]),
        ], location=(200, -10))
    p2.add_layout(legend, 'below')

    p2.lod_timeout
    
    p2.legend.click_policy="hide"
    p2.legend.orientation = "horizontal"

    p2.title.text_font_size = '11pt'
    
    return p2

def rr(attributes):
    def python_callback(event):
   source.data.update(source1.data)
   plot_line = make_plotLine(source, title, subtitle, yunits)
    plot_line.title.text = title
    plot_bar.title.text = titlebar

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<im2.png><im1.png>

Thanks for suggestion. I don’t know why appear the horizontal additional line with value zero although i set visible condition depending of number of columns in the basic and updated dataframe.

Is there simple solution to create plot lines and legend with real variable names (like total, names, females instead generated by me - var1, var2, …) for my data example.
Best regards,

GOran

···

On Thursday, March 7, 2019 at 9:38:59 PM UTC+1, Bryan Van de ven wrote:

Hi,

You are already adding a Legend and configuring its items manually, you will have to clear out Legend.items of the existing legend that you added, and re-configure .items with the new contents you want to see.

Thanks,

Bryan

On Mar 7, 2019, at 12:31 PM, Goran Goki [email protected] wrote:

Hi,

I have dataframe

s4= {‘females’: {‘2012’: 76.9, ‘2007’: 75.9, ‘2005’: 75.9, ‘2014’: 77.5, ‘2004’: 75.8, ‘2000’: 75.2, ‘2013’: 77.5, ‘2006’: 76.2, ‘2002’: 75.6, ‘2008’: 76.5, ‘2010’: 77.2, ‘2001’: 76.1, ‘2011’: 77.2, ‘2003’: 75.7, ‘2009’: 76.7, ‘2015’: 77.4, ‘2016’: 77.5}, ‘males’: {‘2012’: 73.0, ‘2007’: 71.8, ‘2005’: 71.6, ‘2014’: 73.5, ‘2004’: 71.5, ‘2000’: 70.8, ‘2013’: 73.4, ‘2006’: 71.7, ‘2002’: 70.6, ‘2008’: 72.4, ‘2010’: 72.9, ‘2001’: 70.9, ‘2011’: 73.1, ‘2003’: 70.9, ‘2009’: 72.3, ‘2015’: 73.5, ‘2016’: 73.4}, ‘total’: {‘2012’: 74.9, ‘2007’: 73.8, ‘2005’: 73.7, ‘2014’: 75.5, ‘2004’: 73.6, ‘2000’: 73.0, ‘2013’: 75.5, ‘2006’: 73.9, ‘2002’: 73.0, ‘2008’: 74.4, ‘2010’: 75.0, ‘2001’: 73.4, ‘2011’: 75.1, ‘2003’: 73.2, ‘2009’: 74.4, ‘2015’: 75.5, ‘2016’: 75.4}}

with following columns: Years, females, males and total

.

When updating on click button event I get new dataframe

s4= {‘value’: {Timestamp(‘2017-01-01 00:00:00’): nan, Timestamp(‘2015-01-01 00:00:00’): 41.6, Timestamp(‘2001-01-01 00:00:00’): nan, Timestamp(‘2002-01-01 00:00:00’): nan, Timestamp(‘2011-01-01 00:00:00’): 50.4, Timestamp(‘2004-01-01 00:00:00’): nan, Timestamp(‘2014-01-01 00:00:00’): 43.3, Timestamp(‘2005-01-01 00:00:00’): nan, Timestamp(‘2009-01-01 00:00:00’): nan, Timestamp(‘2010-01-01 00:00:00’): 47.2, Timestamp(‘2007-01-01 00:00:00’): nan, Timestamp(‘2016-01-01 00:00:00’): 41.1, Timestamp(‘2008-01-01 00:00:00’): nan, Timestamp(‘2003-01-01 00:00:00’): nan, Timestamp(‘2013-01-01 00:00:00’): 48.1, Timestamp(‘2000-01-01 00:00:00’): nan, Timestamp(‘2012-01-01 00:00:00’): 50.3, Timestamp(‘2006-01-01 00:00:00’): nan}}

with following columns: Years, value.

The question is how to show in first time plot with 3 lines (from dataframe df1) and appropriate legend and after updating to show in the same figure plot with one line (dataframe df2) and appropriate legend.

I tried to define one column data source with same structure (columns: Year, Value, var1, var2, var3, var4 ) but I have a problem to showin the plot figure because in both cases plot shows aditional line with values 0. (see im1 and im 2 in attachment) For im1 columndatasource looks like {‘var4’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘Value’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘var1’: [75.2, 76.1, 75.6, 75.7, 75.8, 75.9, 76.2, 75.9, 76.5, 76.7, 77.2, 77.2, 76.9, 77.5, 77.5, 77.4, 77.5], ‘var2’: [70.8, 70.9, 70.6, 70.9, 71.5, 71.6, 71.7, 71.8, 72.4, 72.3, 72.9, 73.1, 73.0, 73.4, 73.5, 73.5, 73.4], ‘Year’: [‘2000’, ‘2001’, ‘2002’, ‘2003’, ‘2004’, ‘2005’, ‘2006’, ‘2007’, ‘2008’, ‘2009’, ‘2010’, ‘2011’, ‘2012’, ‘2013’, ‘2014’, ‘2015’, ‘2016’], ‘var3’: [73.0, 73.4, 73.0, 73.2, 73.6, 73.7, 73.9, 73.8, 74.4, 74.4, 75.0, 75.1, 74.9, 75.5, 75.5, 75.5, 75.4]} and for im2 Column data source looks like {‘Value’: [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 47.2, 50.4, 50.3, 48.1, 43.3, 41.6, 41.1, nan], ‘var4’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘Year’: [Timestamp(‘2000-01-01 00:00:00’), Timestamp(‘2001-01-01 00:00:00’), Timestamp(‘2002-01-01 00:00:00’), Timestamp(‘2003-01-01 00:00:00’), Timestamp(‘2004-01-01 00:00:00’), Timestamp(‘2005-01-01 00:00:00’), Timestamp(‘2006-01-01 00:00:00’), Timestamp(‘2007-01-01 00:00:00’), Timestamp(‘2008-01-01 00:00:00’), Timestamp(‘2009-01-01 00:00:00’), Timestamp(‘2010-01-01 00:00:00’), Timestamp(‘2011-01-01 00:00:00’), Timestamp(‘2012-01-01 00:00:00’), Timestamp(‘2013-01-01 00:00:00’), Timestamp(‘2014-01-01 00:00:00’), Timestamp(‘2015-01-01 00:00:00’), Timestamp(‘2016-01-01 00:00:00’), Timestamp(‘2017-01-01 00:00:00’)], ‘var1’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘var3’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], ‘var2’: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}

Below is part of the code I use for generating plot line with appropriate legend.
Please help

Thanks,

Goran

s4= {‘females’: {‘2012’: 76.9, ‘2007’: 75.9, ‘2005’: 75.9, ‘2014’: 77.5, ‘2004’: 75.8, ‘2000’: 75.2, ‘2013’: 77.5, ‘2006’: 76.2, ‘2002’: 75.6, ‘2008’: 76.5, ‘2010’: 77.2, ‘2001’: 76.1, ‘2011’: 77.2, ‘2003’: 75.7, ‘2009’: 76.7, ‘2015’: 77.4, ‘2016’: 77.5}, ‘males’: {‘2012’: 73.0, ‘2007’: 71.8, ‘2005’: 71.6, ‘2014’: 73.5, ‘2004’: 71.5, ‘2000’: 70.8, ‘2013’: 73.4, ‘2006’: 71.7, ‘2002’: 70.6, ‘2008’: 72.4, ‘2010’: 72.9, ‘2001’: 70.9, ‘2011’: 73.1, ‘2003’: 70.9, ‘2009’: 72.3, ‘2015’: 73.5, ‘2016’: 73.4}, ‘total’: {‘2012’: 74.9, ‘2007’: 73.8, ‘2005’: 73.7, ‘2014’: 75.5, ‘2004’: 73.6, ‘2000’: 73.0, ‘2013’: 75.5, ‘2006’: 73.9, ‘2002’: 73.0, ‘2008’: 74.4, ‘2010’: 75.0, ‘2001’: 73.4, ‘2011’: 75.1, ‘2003’: 73.2, ‘2009’: 74.4, ‘2015’: 75.5, ‘2016’: 75.4}}

if len(list(s4.columns)) == 1:

    source = ColumnDataSource(data=dict(Year=list(s4.index),
                                        Value=list(s4[list(s4.columns)[0]]),
                                        var1=[0]*len(list(s4.index)),
                                        var2=[0]*len(list(s4.index)),
                                        var3=[0]*len(list(s4.index)),
                                        var4=[0]*len(list(s4.index))))
elif len(list(s4.columns)) == 2:
    source = ColumnDataSource(data=dict(Year=list(s4.index),
                                        Value=[0]*len(list(s4.index)),
                                        var1=list(s4[list(s4.columns)[0]]),
                                        var2=list(s4[list(s4.columns)[1]]),
                                        var3=[0]*len(list(s4.index)),
                                        var4=[0]*len(list(s4.index))))
elif len(list(s4.columns)) == 3:
    source = ColumnDataSource(data=dict(Year=list(s4.index),
                                        Value=[0]*len(list(s4.index)),
                                        var1=list(s4[list(s4.columns)[0]]),
                                        var2=list(s4[list(s4.columns)[1]]),
                                        var3=list(s4[list(s4.columns)[2]]),
                                        var4=[0]*len(list(s4.index))))
elif len(list(s4.columns)) == 4:
    source = ColumnDataSource(data=dict(Year=list(s4.index),
                                        Value=[0]*len(list(s4.index)),
                                        var1=list(s4[list(s4.columns)[0]]),
                                        var2=list(s4[list(s4.columns)[1]]),
                                        var3=list(s4[list(s4.columns)[2]]),
                                        var4=list(s4[list(s4.columns)[3]])))

def make_plotLine(source, title, subtitle, yunits):

cols = list(s4.columns)
b= ['0']*(4 - len(cols))
cols.extend(b)
if list(s4.columns) == 1:
    b= ['0']*(4 - len(cols))
    cols.extend(b)
elif list(s4.columns) == 2:
    cols.insert(0, "0")
    b= ['0']*(4 - len(cols))
    cols.extend(b)
elif list(s4.columns) == 3:
    cols.insert(0, "0")
    b= ['0']*(4 - len(cols))
    cols.extend(b)
elif list(s4.columns) == 4:
    cols.insert(0, "0")
    b= ['0']*(4 - len(cols))
    cols.extend(b)
color = ['red', 'blue', 'green', 'orange']
colors = color[:len(s4.columns)]
p2 = figure(x_axis_type="datetime", title=title, plot_width=800, plot_height=500)
p21 = p2.line(x='Year', y='Value', source=source, line_width=4, alpha=0.5, color=color[0])
p22 = p2.line(x='Year', y='var1', source=source, line_width=4, alpha=0.5, color=color[0])
p23 = p2.line(x='Year', y='var2', source=source, line_width=4, alpha=0.5, color=color[1])
p24 = p2.line(x='Year', y='var3', source=source, line_width=4, alpha=0.5, color=color[2])
p25 = p2.line(x='Year', y='var4', source=source, line_width=4, alpha=0.5, color=color[3])
if list(s4.columns) == 1:
    p21.visible = True
    p22.visible = False
    p23.visible = False
    p24.visible = False
    p25.visible = False
elif list(s4.columns) == 2:
    p21.visible = False
    p22.visible = True
    p23.visible = True
    p24.visible = False
    p25.visible = False
elif list(s4.columns) == 3:
    p21.visible = False
    p22.visible = True
    p23.visible = True
    p24.visible = True
    p25.visible = False
elif list(s4.columns) == 4:
    p21.visible = False
    p22.visible = True
    p23.visible = True
    p24.visible = True
    p25.visible = True
p2.xaxis.axis_label = None
p2.yaxis.axis_label = yunits
p2.x_range = DataRange1d(range_padding=0.1)
p2.grid.grid_line_alpha = 0.3
p2.xaxis.formatter=DatetimeTickFormatter(
    years=["%Y"]
    )
p2.min_border_bottom = 0
p2.yaxis.minor_tick_line_color = None
p2.legend.location = "bottom_right"
legend = Legend(items=[
    (cols[0]   , [p22]),
    (cols[1] , [p23]),
    (cols[2] , [p24]),
    (cols[3] , [p25]),
    ], location=(200, -10))
p2.add_layout(legend, 'below')
p2.lod_timeout
p2.legend.click_policy="hide"
p2.legend.orientation = "horizontal"
p2.title.text_font_size = '11pt'
return p2

def rr(attributes):

def python_callback(event):

source.data.update(source1.data)

plot_line = make_plotLine(source, title, subtitle, yunits)

plot_line.title.text = title
plot_bar.title.text = titlebar


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<im2.png><im1.png>

Hi,

The legend displays everything in .items, regardless of glyphs visibility. You are already setting the items once, if you want to update the contents of the legend later, then you need to set

  plot.legend.items = [ new items for legend ]

Thanks,

Bryan

···

On Mar 7, 2019, at 1:49 PM, Goran Goki <[email protected]> wrote:

Thanks for suggestion. I don't know why appear the horizontal additional line with value zero although i set visible condition depending of number of columns in the basic and updated dataframe.

Is there simple solution to create plot lines and legend with real variable names (like total, names, females instead generated by me - var1, var2, ...) for my data example.
Best regards,
GOran

On Thursday, March 7, 2019 at 9:38:59 PM UTC+1, Bryan Van de ven wrote:
Hi,

You are already adding a Legend and configuring its items manually, you will have to clear out Legend.items of the existing legend that you added, and re-configure .items with the new contents you want to see.

Thanks,

Bryan

> On Mar 7, 2019, at 12:31 PM, Goran Goki <[email protected]> wrote:
>
> Hi,
>
> I have dataframe
>
> s4= {'females': {'2012': 76.9, '2007': 75.9, '2005': 75.9, '2014': 77.5, '2004': 75.8, '2000': 75.2, '2013': 77.5, '2006': 76.2, '2002': 75.6, '2008': 76.5, '2010': 77.2, '2001': 76.1, '2011': 77.2, '2003': 75.7, '2009': 76.7, '2015': 77.4, '2016': 77.5}, 'males': {'2012': 73.0, '2007': 71.8, '2005': 71.6, '2014': 73.5, '2004': 71.5, '2000': 70.8, '2013': 73.4, '2006': 71.7, '2002': 70.6, '2008': 72.4, '2010': 72.9, '2001': 70.9, '2011': 73.1, '2003': 70.9, '2009': 72.3, '2015': 73.5, '2016': 73.4}, 'total': {'2012': 74.9, '2007': 73.8, '2005': 73.7, '2014': 75.5, '2004': 73.6, '2000': 73.0, '2013': 75.5, '2006': 73.9, '2002': 73.0, '2008': 74.4, '2010': 75.0, '2001': 73.4, '2011': 75.1, '2003': 73.2, '2009': 74.4, '2015': 75.5, '2016': 75.4}}
>
> with following columns: Years, females, males and total
> .
> When updating on click button event I get new dataframe
> s4= {'value': {Timestamp('2017-01-01 00:00:00'): nan, Timestamp('2015-01-01 00:00:00'): 41.6, Timestamp('2001-01-01 00:00:00'): nan, Timestamp('2002-01-01 00:00:00'): nan, Timestamp('2011-01-01 00:00:00'): 50.4, Timestamp('2004-01-01 00:00:00'): nan, Timestamp('2014-01-01 00:00:00'): 43.3, Timestamp('2005-01-01 00:00:00'): nan, Timestamp('2009-01-01 00:00:00'): nan, Timestamp('2010-01-01 00:00:00'): 47.2, Timestamp('2007-01-01 00:00:00'): nan, Timestamp('2016-01-01 00:00:00'): 41.1, Timestamp('2008-01-01 00:00:00'): nan, Timestamp('2003-01-01 00:00:00'): nan, Timestamp('2013-01-01 00:00:00'): 48.1, Timestamp('2000-01-01 00:00:00'): nan, Timestamp('2012-01-01 00:00:00'): 50.3, Timestamp('2006-01-01 00:00:00'): nan}}
>
> with following columns: Years, value.
>
> The question is how to show in first time plot with 3 lines (from dataframe df1) and appropriate legend and after updating to show in the same figure plot with one line (dataframe df2) and appropriate legend.
> I tried to define one column data source with same structure (columns: Year, Value, var1, var2, var3, var4 ) but I have a problem to showin the plot figure because in both cases plot shows aditional line with values 0. (see im1 and im 2 in attachment) For im1 columndatasource looks like {'var4': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'Value': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'var1': [75.2, 76.1, 75.6, 75.7, 75.8, 75.9, 76.2, 75.9, 76.5, 76.7, 77.2, 77.2, 76.9, 77.5, 77.5, 77.4, 77.5], 'var2': [70.8, 70.9, 70.6, 70.9, 71.5, 71.6, 71.7, 71.8, 72.4, 72.3, 72.9, 73.1, 73.0, 73.4, 73.5, 73.5, 73.4], 'Year': ['2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013', '2014', '2015', '2016'], 'var3': [73.0, 73.4, 73.0, 73.2, 73.6, 73.7, 73.9, 73.8, 74.4, 74.4, 75.0, 75.1, 74.9, 75.5, 75.5, 75.5, 75.4]} and for im2 Column data source looks like {'Value': [nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, 47.2, 50.4, 50.3, 48.1, 43.3, 41.6, 41.1, nan], 'var4': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'Year': [Timestamp('2000-01-01 00:00:00'), Timestamp('2001-01-01 00:00:00'), Timestamp('2002-01-01 00:00:00'), Timestamp('2003-01-01 00:00:00'), Timestamp('2004-01-01 00:00:00'), Timestamp('2005-01-01 00:00:00'), Timestamp('2006-01-01 00:00:00'), Timestamp('2007-01-01 00:00:00'), Timestamp('2008-01-01 00:00:00'), Timestamp('2009-01-01 00:00:00'), Timestamp('2010-01-01 00:00:00'), Timestamp('2011-01-01 00:00:00'), Timestamp('2012-01-01 00:00:00'), Timestamp('2013-01-01 00:00:00'), Timestamp('2014-01-01 00:00:00'), Timestamp('2015-01-01 00:00:00'), Timestamp('2016-01-01 00:00:00'), Timestamp('2017-01-01 00:00:00')], 'var1': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'var3': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'var2': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}
>
> Below is part of the code I use for generating plot line with appropriate legend.
> Please help
> Thanks,
> Goran
>
> s4= {'females': {'2012': 76.9, '2007': 75.9, '2005': 75.9, '2014': 77.5, '2004': 75.8, '2000': 75.2, '2013': 77.5, '2006': 76.2, '2002': 75.6, '2008': 76.5, '2010': 77.2, '2001': 76.1, '2011': 77.2, '2003': 75.7, '2009': 76.7, '2015': 77.4, '2016': 77.5}, 'males': {'2012': 73.0, '2007': 71.8, '2005': 71.6, '2014': 73.5, '2004': 71.5, '2000': 70.8, '2013': 73.4, '2006': 71.7, '2002': 70.6, '2008': 72.4, '2010': 72.9, '2001': 70.9, '2011': 73.1, '2003': 70.9, '2009': 72.3, '2015': 73.5, '2016': 73.4}, 'total': {'2012': 74.9, '2007': 73.8, '2005': 73.7, '2014': 75.5, '2004': 73.6, '2000': 73.0, '2013': 75.5, '2006': 73.9, '2002': 73.0, '2008': 74.4, '2010': 75.0, '2001': 73.4, '2011': 75.1, '2003': 73.2, '2009': 74.4, '2015': 75.5, '2016': 75.4}}
>
>
>
>
>
> if len(list(s4.columns)) == 1:
> source = ColumnDataSource(data=dict(Year=list(s4.index),
> Value=list(s4[list(s4.columns)[0]]),
> var1=[0]*len(list(s4.index)),
> var2=[0]*len(list(s4.index)),
> var3=[0]*len(list(s4.index)),
> var4=[0]*len(list(s4.index))))
>
> elif len(list(s4.columns)) == 2:
> source = ColumnDataSource(data=dict(Year=list(s4.index),
> Value=[0]*len(list(s4.index)),
> var1=list(s4[list(s4.columns)[0]]),
> var2=list(s4[list(s4.columns)[1]]),
> var3=[0]*len(list(s4.index)),
> var4=[0]*len(list(s4.index))))
> elif len(list(s4.columns)) == 3:
> source = ColumnDataSource(data=dict(Year=list(s4.index),
> Value=[0]*len(list(s4.index)),
> var1=list(s4[list(s4.columns)[0]]),
> var2=list(s4[list(s4.columns)[1]]),
> var3=list(s4[list(s4.columns)[2]]),
> var4=[0]*len(list(s4.index))))
> elif len(list(s4.columns)) == 4:
> source = ColumnDataSource(data=dict(Year=list(s4.index),
> Value=[0]*len(list(s4.index)),
> var1=list(s4[list(s4.columns)[0]]),
> var2=list(s4[list(s4.columns)[1]]),
> var3=list(s4[list(s4.columns)[2]]),
> var4=list(s4[list(s4.columns)[3]])))
>
>
> def make_plotLine(source, title, subtitle, yunits):
> cols = list(s4.columns)
> b= ['0']*(4 - len(cols))
> cols.extend(b)
>
>
> if list(s4.columns) == 1:
> b= ['0']*(4 - len(cols))
> cols.extend(b)
> elif list(s4.columns) == 2:
> cols.insert(0, "0")
> b= ['0']*(4 - len(cols))
> cols.extend(b)
>
> elif list(s4.columns) == 3:
> cols.insert(0, "0")
> b= ['0']*(4 - len(cols))
> cols.extend(b)
>
> elif list(s4.columns) == 4:
> cols.insert(0, "0")
> b= ['0']*(4 - len(cols))
> cols.extend(b)
>
>
> color = ['red', 'blue', 'green', 'orange']
> colors = color[:len(s4.columns)]
>
>
> p2 = figure(x_axis_type="datetime", title=title, plot_width=800, plot_height=500)
>
> p21 = p2.line(x='Year', y='Value', source=source, line_width=4, alpha=0.5, color=color[0])
> p22 = p2.line(x='Year', y='var1', source=source, line_width=4, alpha=0.5, color=color[0])
> p23 = p2.line(x='Year', y='var2', source=source, line_width=4, alpha=0.5, color=color[1])
> p24 = p2.line(x='Year', y='var3', source=source, line_width=4, alpha=0.5, color=color[2])
> p25 = p2.line(x='Year', y='var4', source=source, line_width=4, alpha=0.5, color=color[3])
>
> if list(s4.columns) == 1:
> p21.visible = True
> p22.visible = False
> p23.visible = False
> p24.visible = False
> p25.visible = False
>
> elif list(s4.columns) == 2:
> p21.visible = False
> p22.visible = True
> p23.visible = True
> p24.visible = False
> p25.visible = False
>
> elif list(s4.columns) == 3:
> p21.visible = False
> p22.visible = True
> p23.visible = True
> p24.visible = True
> p25.visible = False
>
> elif list(s4.columns) == 4:
> p21.visible = False
> p22.visible = True
> p23.visible = True
> p24.visible = True
> p25.visible = True
>
>
>
>
> p2.xaxis.axis_label = None
> p2.yaxis.axis_label = yunits
> p2.x_range = DataRange1d(range_padding=0.1)
> p2.grid.grid_line_alpha = 0.3
> p2.xaxis.formatter=DatetimeTickFormatter(
> years=["%Y"]
> )
> p2.min_border_bottom = 0
> p2.yaxis.minor_tick_line_color = None
>
> p2.legend.location = "bottom_right"
>
> legend = Legend(items=[
> (cols[0] , [p22]),
> (cols[1] , [p23]),
> (cols[2] , [p24]),
> (cols[3] , [p25]),
> ], location=(200, -10))
> p2.add_layout(legend, 'below')
>
>
> p2.lod_timeout
>
> p2.legend.click_policy="hide"
> p2.legend.orientation = "horizontal"
>
> p2.title.text_font_size = '11pt'
>
> return p2
>
> def rr(attributes):
> def python_callback(event):
> source.data.update(source1.data)
> plot_line = make_plotLine(source, title, subtitle, yunits)
> plot_line.title.text = title
> plot_bar.title.text = titlebar
>
>
>
>
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> <im2.png><im1.png>

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