How to display a Folium Map within a for loop in a Jupyter Notebook ?

Examples of how to display a Folium Map within a for loop in a Jupyter Notebook

Using folium display() function

Creating a Folium map in a Jupyter Notebook is fairly straightforward. Here is a common example of how to do that

import folium

m = folium.Map(location=[0, 0], zoom_start=2)

m

Another solution for displaying a map is to use the display() function.

import folium

m = folium.Map(location=[0, 0], zoom_start=2)

display(m)

That can be used within a for loop:

for i in range(3):

    m = folium.Map(location=[0, 0], zoom_start=2)

    display(m)

Example

Below is an example where we iterate through several images and ask if they contain a solar panel farm

import folium
import pandas as pd
import numpy as np

from IPython.display import clear_output

data = np.array([[349, 3820, 27.839248657226562, 116.39884185791016, 367.0,
        287.5710754394531, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
        15.865395545959473, 1.8201713562011719, 0.568378746509552, 1, 0,
        0, 7, 1, 45.845672607421875, -154.86322021484375,
        18.851022720336914, 80.26931762695312, 0, 'Day',
        0.523607075214386, 1.0820577144622803, 1.600000023841858],
       [649, 3823, 28.80352210998535, 116.09571838378906, 367.0,
        297.1990051269531, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
        10.88183879852295, 1.5843127965927124, 0.7265815734863281, 0, 0,
        0, 7, 1, 46.636558532714844, -155.5345001220703,
        18.935832977294922, 78.32439422607422, 0, 'Day',
        0.5620156526565552, 1.0661375522613525, 1.600000023841858],
       [785, 3784, 29.274351119995117, 116.13337707519531,
        344.3221130371094, 295.54931640625, 305.1109924316406,
        295.8750915527344, 9.235969543457031, 3.505326271057129,
        1.9297815561294556, 1.5755447149276733, 14.316523551940918,
        2.989433526992798, 0.6907815933227539, 0, 0, 10, 8, 1,
        47.089637756347656, -155.63401794433594, 17.746267318725586,
        79.08007049560547, 0, 'Day', 0.8018679022789001,
        1.5472339391708374, 1.267532467842102],
       [787, 3784, 29.281211853027344, 116.13185119628906,
        354.74627685546875, 297.3043212890625, 305.18701171875,
        295.8792724609375, 9.307778358459473, 3.5285837650299072,
        1.9626555442810059, 1.5659282207489014, 13.985917091369629,
        4.0554094314575195, 0.6870543360710144, 0, 0, 10, 8, 1,
        47.095340728759766, -155.63851928710938, 17.746490478515625,
        79.26925659179688, 0, 'Day', 0.5754696130752563,
        1.2988111972808838, 1.517224907875061],
       [927, 3836, 29.697757720947266, 115.77227020263672, 367.0,
        295.2755432128906, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
        7.547194480895996, 2.4319303035736084, 0.6598378419876099, 1, 0,
        0, 7, 1, 47.35850143432617, -156.20074462890625,
        19.34339141845703, 80.09915924072266, 0, 'Day',
        0.7618721723556519, 1.1604864597320557, 1.600000023841858]],
      dtype=object)

dfsp = pd.DataFrame(data=data, columns = ['FP_line',
 'FP_sample',
 'FP_latitude',
 'FP_longitude',
 'FP_T4',
 'FP_T5',
 'FP_MeanT4',
 'FP_MeanT5',
 'FP_MeanDT',
 'FP_MAD_T4',
 'FP_MAD_T5',
 'FP_MAD_DT',
 'FP_power',
 'FP_Rad13',
 'FP_MeanRad13',
 'FP_AdjCloud',
 'FP_AdjWater',
 'FP_WinSize',
 'FP_confidence',
 'FP_day',
 'FP_SolZenAng',
 'FP_SolAzAng',
 'FP_ViewZenAng',
 'FP_ViewAzAng',
 'FP_PersistentAnomalyCategory',
 'Day_Night_Flag',
 'T1',
 'T2',
 'T3'])

for index, row in dfsp.iterrows():

    m = folium.Map(location=[0, 0], zoom_start=17)

    long = row['FP_longitude']
    lat = row['FP_latitude']

    print(long,lat)

    m = folium.Map([lat,long], zoom_start=17)

    folium.TileLayer(
            tiles = 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}',
            attr = 'Esri',
            name = 'Esri Satellite',
            overlay = False,
            control = True
           ).add_to(m)

    folium.Marker(
        location=[lat, long],
        popup="Mt. Hood Meadows",
        icon=folium.Icon(icon="cloud"),
    ).add_to(m)

    display(m)

    value = input('Input a value. Type x to quit.')

    clear_output(wait=True)

References