添加 Bokeh Slider 以按年份可视化 GIS 数据

Adding Bokeh Slider to visualise GIS data by year

我正在尝试可视化从 GIS 导入的数据。大约有 70 个点,每个点都有地名和年份数据以及每个给定年份的值。

     name       year    mean    geometry
0    Place 1    2008    105816    POINT (253662.995 663270.013)
1    Place 1    2009    94381    POINT (253662.995 663270.013)
2    Place 1    2010    101280    POINT (253662.995 663270.013)
3    Place 1    2011    86664    POINT (253662.995 663270.013)
4    Place 1    2012    83828    POINT (253662.995 663270.013)
5    Place 1    2013    91433    POINT (253662.995 663270.013)
6    Place 1    2014    90971    POINT (253662.995 663270.013)
7    Place 1    2015    140151    POINT (253662.995 663270.013)
8    Place 1    2016    104499    POINT (253662.995 663270.013)
9    Place 1    2017    110172    POINT (253662.995 663270.013)
10    Place 1    2018    111700    POINT (253662.995 663270.013)
11    Place 2    2008    99176    POINT (262062.995 669070.013)
12    Place 2    2009    101865    POINT (262062.995 669070.013)
13    Place 2    2010    80560    POINT (262062.995 669070.013)
14    Place 2    2011    61915    POINT (262062.995 669070.013)
15    Place 2    2012    74723    POINT (262062.995 669070.013)
16    Place 2    2013    71550    POINT (262062.995 669070.013)
17    Place 2    2014    239955    POINT (262062.995 669070.013)
18    Place 2    2015    93824    POINT (262062.995 669070.013)
19    Place 2    2016    71751    POINT (262062.995 669070.013)
20    Place 2    2017    86586    POINT (262062.995 669070.013)
21    Place 2    2018    74684    POINT (262062.995 669070.013)
22    Place 3    2008    180296    POINT (251662.995 663270.013)
23    Place 3    2009    165689    POINT (251662.995 663270.013)
24    Place 3    2010    175376    POINT (251662.995 663270.013)

我想使用滑块可视化数据以仅显示具有所选年份值的点。

这就是我正在做的

def getPointCoords(row, geom, coord_type):
    """Calculates coordinates ('x' or 'y') of a Point geometry"""
    if coord_type == 'x':
        return row[geom].x
    elif coord_type == 'y':
        return row[geom].y

# Calculate x and y coordinates of the points

stations['x'] = stations.apply(getPointCoords, geom='geometry', coord_type='x', axis=1)
stations['y'] = stations.apply(getPointCoords, geom='geometry', coord_type='y', axis=1)

# Make a copy, drop the geometry column and create ColumnDataSource
st_df = stations.drop('geometry', axis=1).copy()
stsource = ColumnDataSource(st_df)

#colour based on mean value
colormap = LinearColorMapper(palette='Magma256', low=min(stsource.data['mean']),high=max(stsource.data['mean']))

p= figure(plot_height=400, plot_width=400)
p.circle(x="x", y="y", source=stsource,color = {'field': 'mean', 'transform': colormap})

# Define the callback function: update_plot
def update_plot(attr, old, new):
    # Set the year name to slider.value and new_data to source.data
    year = slider.value
    new_data = {
        'x'       : stsource.data['year'].x,
        'y'       :stsource.data['year'].y,
        'mean' : stsource.data['year'].mean,

    }
    stsource.data = new_data


# Make a slider object: slider
slider = Slider(title = 'slider', start = 2008, end = 2020, step = 1, value = 2012)

# Attach the callback to the 'value' property of slider
slider.on_change('value', update_plot)

# Make a row layout of widgetbox(slider) and plot and add it to the current document
layout = row(widgetbox(slider), p)
curdoc().add_root(layout)

这是我得到的结果

我看到了所有的点(很好!)但是当我吸尘器时我也看到了所有的值。
这部分似乎不起作用,但我不明白为什么。

# Define the callback function: update_plot
def update_plot(attr, old, new):
    # Set the year name to slider.value and new_data to source.data
    year = slider.value
    new_data = {
        'x'       : stsource.data['year'].x,
        'y'       :stsource.data['year'].y,
        'mean' : stsource.data['year'].mean,

    }
    stsource.data = new_data

请帮忙! 谢谢。

这最终对我有用

# Define the callback function: update_plot
def update_plot(attr, old, new):
    # Set the year name to slider.value and new_data to source.data
    year = slider.value
    stsource.data  = st_df[st_df.year == year]

我意识到,由于我的数据的性质,我不需要单独更新 x、y,因为它们始终相同,但只有一个 'mean' 值。 所以对我来说最简单的似乎是根据年份值更新源数据。