[FIXED] How to add up more data in an existing plotly graph?

Issue

I have successfully plotted the below data using plotly from an Excel file.

Here is my code:

file_loc1 = "AgeGroupData_time_to_treatment.xlsx"

df_centroid_CoordNew = pd.read_excel(file_loc1, index_col=None, na_values=['NA'], usecols="C:D,AB")
df_centroid_CoordNew.head()

df_centroid_Coord['Ambulance_Treatment_Time'] = df_centroid_Coord ['Base_TT']

fig = px.scatter(df_centroid_Coord, x="x", y="y", 
                 title="Southern Region Centroids", 
                 color='Ambulance_Treatment_Time', 
                 hover_name="KnNamn",
                 hover_data= ['Ambulance_Treatment_Time', "TotPop"],
                 log_x=True, size_max=60, 
                 color_continuous_scale='Reds', range_color=(0.5,2), width=1250, height=1000)

fig.update_traces(marker={'size': 8, 'symbol': 1})
#fig.update_traces(marker={'symbol': 1})
fig.update_layout(paper_bgcolor="LightSteelBlue")

fig.show()

The shapes of the plotted data points are square.

Here is output of my code:

Now, I want to plot more data points in circle or any shapes on the same plotly graph by reading an excel file. Please have a look at the data below.

How I can add up the new data to an existing graph in plotly?

Map data with total population and treatment time (Base_TT):

    ID  KnNamn  x   y   TotPop  Base_TT
1   2   Växjö   14.662290   57.027520   9   1.599971
2   3   Bromölla    14.494072   56.065635   264 1.307165
3   4   Trelleborg  13.219968   55.478675   40  1.411554
4   5   Tomelilla   14.005013   55.721209   6   1.968138
5   6   Halmstad    12.737361   56.710973   386 1.309849
6   7   Alvesta 14.566685   56.748729   47  1.719117
7   8   Laholm  13.241388   56.413591   0   2.000620
8   9   Tingsryd    14.943081   56.542837   16  1.668725
9   10  Sölvesborg  14.574474   56.056953   1147    1.266862
10  11  Halmstad    13.068009   56.635666   38  1.589239
11  12  Tingsryd    14.699642   56.479597   3   1.960050
12  13  Vellinge    13.029769   55.484749   61  1.254957
13  14  Örkelljunga 13.169010   56.232819   12  1.429789
14  15  Svalöv  13.059068   55.853696   26  1.553722
15  16  Sjöbo   13.738205   55.601936   6   1.326429
16  17  Hässleholm  13.729872   56.347672   13  1.709021
17  18  Olofström   14.588037   56.290604   6   1.444833
18  19  Eslöv   13.168712   55.900311   3   1.527547
19  20  Ronneby 15.024222   56.273317   3   1.692005
20  21  Ängelholm   12.910101   56.246689   19  1.090544

Ambulance Data:

    ID  Ambulance station name  Longtitude  Latitude
    0   1   Älmhult 14.128734   56.547992
    1   2   Ängelholm   12.870739   56.242114
    2   3   Alvesta 14.549503   56.920740
    3   4   Östra Ljungby   13.057450   56.188099
    4   5   Broby   14.080958   56.254481
    5   6   Bromölla    14.466869   56.072272
    6   7   Förslöv 12.814913   56.350098
    7   9   Hässleholm  13.778234   56.161536
    8   10  Höganäs 12.556995   56.206016
    9   11  Hörby   13.643265   55.849811
    10  12  Halmstad, Väster    12.819960   56.674306
    11  13  Halmstad, Öster 12.882289   56.676871
    12  14  Helsingborg 12.738642   56.084708
    13  15  Hyltebruk   13.238277   56.993058
    14  16  Karlshamn   14.854022   56.186596
    15  17  Karlskrona  15.606300   56.183054
    16  18  Kristianstad    14.171371   56.031201
    17  20  Löddeköpinge    12.995037   55.766946
    18  21  Laholm  13.033763   56.498955
    19  22  Landskrona  12.867245   55.872659
    20  23  Lenhovda    15.283913   57.001953
    21  24  Lessebo 15.267357   56.756860
    22  25  Ljungby 13.935399   56.835023
    23  26  Lund    13.226607   55.695212
    24  27  Markaryd    13.591491   56.452057
    25  28  Olofström   14.545848   56.272221
    26  29  Osby    13.983674   56.384833
    27  30  Perstorp    13.388304   56.130752
    28  31  Ronneby 15.280554   56.211863
    29  32  Sölvesborg  14.570503   56.052113
    30  33  Simrishamn  14.338632   55.552765

Merged Dataset for plotting

KnNamn  x   y   TotPop  Base_TT Ambulance station name  Longtitude  Latitude
Växjö   14.66229    57.02752    9   1.599971    Ängelholm   12.87074    56.24211
Bromölla    14.49407    56.06564    264 1.307165    Alvesta 14.5495 56.92074
Trelleborg  13.21997    55.47868    40  1.411554    Östra Ljungby   13.05745    56.1881
Tomelilla   14.00501    55.72121    6   1.968138    Broby   14.08096    56.25448
Halmstad    12.73736    56.71097    386 1.309849            
Alvesta 14.56669    56.74873    47  1.719117            
Laholm  13.24139    56.41359    0   2.00062         
Tingsryd    14.94308    56.54284    16  1.668725    

    


        

Solution

If the data is the same but the column names are different, aligning to either column name is fine for the data for the chart. Add a graph with a graph object by reusing the graph data created with plotly.express. First I added a chart that was already completed, then a chart with latitude and longitude. Station names and locations are drawn using scatterplot markers and text mode.

df_station.rename(columns={'Longtitude':'x', 'Latitude':'y'}, inplace=True)

import plotly.express as px
import plotly.graph_objects as go

df_centroid_Coord['Ambulance_Treatment_Time'] = df_centroid_Coord ['Base_TT']

sca = px.scatter(df_centroid_Coord, x="x", y="y", 
                 title="Southern Region Centroids", 
                 color='Ambulance_Treatment_Time', 
                 hover_name="KnNamn",
                 #hover_data= ['Ambulance_Treatment_Time', "TotPop"],
                 log_x=True,
                 size_max=60, 
                 color_continuous_scale='Reds',
                 range_color=(0.5,2),
                 )

sca.update_traces(marker={'size': 8, 'symbol': 1})

fig = go.Figure()
fig.add_trace(go.Scatter(sca.data[0]))
fig.add_trace(go.Scatter(x=df_station['x'],
                         y=df_station['y'],
                         mode='markers+text',
                         text=df_station['Ambulance station name'],
                         textposition='top center',
                         showlegend=False,
                         marker=dict(
                             size=5,
                             symbol=2,
                             color='blue'
                         )
                        )
             )
              
#fig.update_traces(marker={'symbol': 1})
fig.update_layout(width=625, height=500, paper_bgcolor="LightSteelBlue")

fig.show()

Answered By - r-beginners