shakasom

# Read the data
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/US-shooting-incidents.csv")

# Let us only take 10 samples
df = df.sample(10)

# One width for all 
pn.widgets.Tabulator(df, widths=130)

# Automatically adjust the columns dependending on their content

shakasom

formatters = {
    'latitude': {'type': 'progress', 'max': 90.00, 'color':'red'},
    'longitude': {'type': 'progress', 'max': 180.00},
    'large': {'type': 'tickCross'},
    
}

pn.widgets.Tabulator(df, formatters=formatters)

shakasom

from bokeh.models.widgets.tables import NumberFormatter, BooleanFormatter

bokeh_formatters = {
    'latitude': NumberFormatter(format='0.00'),
    'large': BooleanFormatter(),
   
}

pn.widgets.Tabulator(df, formatters=bokeh_formatters)

shakasom

import datetime as dt
import numpy as np
import pandas as pd
import panel as pn

pn.extension('tabulator')

df = pd.DataFrame({
    'city': ["A", "B", "C", "D", "E"],
    'latitude': [34.6578, 76.6789, 23.7896, 45.6785, 14.2545],

shakasom

import streamlit as st
import PIL
from exif import Image
from collections import defaultdict
import pandas as pd

st.set_page_config(page_title="Geolocating Photos Application",
                   page_icon="🌍",
                   layout="wide",
                   initial_sidebar_state="expanded")

shakasom

import streamlit as st
import PIL
from exif import Image
from collections import defaultdict

st.set_page_config(page_title="Geolocating Photos Application",
                   page_icon="🌍",
                   layout="wide",
                   initial_sidebar_state="expanded")

shakasom

import streamlit as st
import PIL
from exif import Image

st.set_page_config(page_title="Geolocating Photos Application",
                   page_icon="🌍",
                   layout="wide",
                   initial_sidebar_state="expanded")

shakasom

import streamlit as st
import PIL

st.set_page_config(page_title="Geolocating Photos Application",
                   page_icon="🌍",
                   layout="wide",
                   initial_sidebar_state="expanded")


st.sidebar.title("Geolocating Photos Application")

shakasom

@st.cache(persist=True, suppress_st_warning=True)
def display_map(df):
    px.set_mapbox_access_token(
        "pk.eyJ1Ijoic2hha2Fzb20iLCJhIjoiY2plMWg1NGFpMXZ5NjJxbjhlM2ttN3AwbiJ9.RtGYHmreKiyBfHuElgYq_w"
    )
    fig = px.scatter_mapbox(df, lat="latitude", lon="longitude", zoom=10)
    return fig


def download_csv(df):

shakasom

def geocode(df):
    locator = Nominatim(user_agent="myGeocoder")
    geocode = RateLimiter(locator.geocode, min_delay_seconds=1)
    df["location"] = df["geocode_col"].apply(geocode)
    df["point"] = df["location"].apply(lambda loc: tuple(loc.point) if loc else None)
    df[["latitude", "longitude", "altitude"]] = pd.DataFrame(
        df["point"].tolist(), index=df.index
    )
    return df