Geo

1mask = df['STUSPS'] == 'AK'
227    MULTIPOLYGON (((179.48246 51.98283, 179.48656 ...
3Name: geometry, dtype: geometry
4import geopandas as gpd
5import matplotlib.pyplot as plt
6
7# import the United States shape file 
8df = gpd.read_file('Desktop/cb_2018_us_state_500k/cb_2018_us_state_500k.shp')
9
10# exclude the values that we would not like to display
11exclude = df[~df['STUSPS'].isin(['PR', 'AS', 'VI', 'MP', 'GU','AK'])]
12
13# create a plot figure
14fig, ax = plt.subplots(1, figsize=(20, 10))
15
16exclude.plot(column="NAME", ax=ax)
17_ = ax.set_xlim([-130, -64])
18_ = ax.set_ylim([22, 53])
19 STATEFP   STATENS     AFFGEOID GEOID STUSPS            NAME LSAD  \
200      28  01779790  0400000US28    28     MS     Mississippi   00   
211      37  01027616  0400000US37    37     NC  North Carolina   00   
222      40  01102857  0400000US40    40     OK        Oklahoma   00   
23
24          ALAND       AWATER  \
250  121533519481   3926919758   
261  125923656064  13466071395   
272  177662925723   3374587997   
28
29                                            geometry  
300  MULTIPOLYGON (((-88.50297 30.21523, -88.49176 ...  
311  MULTIPOLYGON (((-75.72681 35.93584, -75.71827 ...  
322  POLYGON ((-103.00257 36.52659, -103.00219 36.6...  
33

1mask = df['STUSPS'] == 'AK'
227    MULTIPOLYGON (((179.48246 51.98283, 179.48656 ...
3Name: geometry, dtype: geometry
4import geopandas as gpd
5import matplotlib.pyplot as plt
6
7# import the United States shape file 
8df = gpd.read_file('Desktop/cb_2018_us_state_500k/cb_2018_us_state_500k.shp')
9
10# exclude the values that we would not like to display
11exclude = df[~df['STUSPS'].isin(['PR', 'AS', 'VI', 'MP', 'GU','AK'])]
12
13# create a plot figure
14fig, ax = plt.subplots(1, figsize=(20, 10))
15
16exclude.plot(column="NAME", ax=ax)
17_ = ax.set_xlim([-130, -64])
18_ = ax.set_ylim([22, 53])
19 STATEFP   STATENS     AFFGEOID GEOID STUSPS            NAME LSAD  \
200      28  01779790  0400000US28    28     MS     Mississippi   00   
211      37  01027616  0400000US37    37     NC  North Carolina   00   
222      40  01102857  0400000US40    40     OK        Oklahoma   00   
23
24          ALAND       AWATER  \
250  121533519481   3926919758   
261  125923656064  13466071395   
272  177662925723   3374587997   
28
29                                            geometry  
300  MULTIPOLYGON (((-88.50297 30.21523, -88.49176 ...  
311  MULTIPOLYGON (((-75.72681 35.93584, -75.71827 ...  
322  POLYGON ((-103.00257 36.52659, -103.00219 36.6...  
33USA_ALS = USA[USA.STUSPS=='AK']
34

1mask = df['STUSPS'] == 'AK'
227    MULTIPOLYGON (((179.48246 51.98283, 179.48656 ...
3Name: geometry, dtype: geometry
4import geopandas as gpd
5import matplotlib.pyplot as plt
6
7# import the United States shape file 
8df = gpd.read_file('Desktop/cb_2018_us_state_500k/cb_2018_us_state_500k.shp')
9
10# exclude the values that we would not like to display
11exclude = df[~df['STUSPS'].isin(['PR', 'AS', 'VI', 'MP', 'GU','AK'])]
12
13# create a plot figure
14fig, ax = plt.subplots(1, figsize=(20, 10))
15
16exclude.plot(column="NAME", ax=ax)
17_ = ax.set_xlim([-130, -64])
18_ = ax.set_ylim([22, 53])
19 STATEFP   STATENS     AFFGEOID GEOID STUSPS            NAME LSAD  \
200      28  01779790  0400000US28    28     MS     Mississippi   00   
211      37  01027616  0400000US37    37     NC  North Carolina   00   
222      40  01102857  0400000US40    40     OK        Oklahoma   00   
23
24          ALAND       AWATER  \
250  121533519481   3926919758   
261  125923656064  13466071395   
272  177662925723   3374587997   
28
29                                            geometry  
300  MULTIPOLYGON (((-88.50297 30.21523, -88.49176 ...  
311  MULTIPOLYGON (((-75.72681 35.93584, -75.71827 ...  
322  POLYGON ((-103.00257 36.52659, -103.00219 36.6...  
33USA_ALS = USA[USA.STUSPS=='AK']
34USA_ALS['geometry'] = USA_ALS.geometry.apply(lambda x: shapely.affinity.translate(x, xoff=0, yoff=-100))
35

1mask = df['STUSPS'] == 'AK'
227    MULTIPOLYGON (((179.48246 51.98283, 179.48656 ...
3Name: geometry, dtype: geometry
4import geopandas as gpd
5import matplotlib.pyplot as plt
6
7# import the United States shape file 
8df = gpd.read_file('Desktop/cb_2018_us_state_500k/cb_2018_us_state_500k.shp')
9
10# exclude the values that we would not like to display
11exclude = df[~df['STUSPS'].isin(['PR', 'AS', 'VI', 'MP', 'GU','AK'])]
12
13# create a plot figure
14fig, ax = plt.subplots(1, figsize=(20, 10))
15
16exclude.plot(column="NAME", ax=ax)
17_ = ax.set_xlim([-130, -64])
18_ = ax.set_ylim([22, 53])
19 STATEFP   STATENS     AFFGEOID GEOID STUSPS            NAME LSAD  \
200      28  01779790  0400000US28    28     MS     Mississippi   00   
211      37  01027616  0400000US37    37     NC  North Carolina   00   
222      40  01102857  0400000US40    40     OK        Oklahoma   00   
23
24          ALAND       AWATER  \
250  121533519481   3926919758   
261  125923656064  13466071395   
272  177662925723   3374587997   
28
29                                            geometry  
300  MULTIPOLYGON (((-88.50297 30.21523, -88.49176 ...  
311  MULTIPOLYGON (((-75.72681 35.93584, -75.71827 ...  
322  POLYGON ((-103.00257 36.52659, -103.00219 36.6...  
33USA_ALS = USA[USA.STUSPS=='AK']
34USA_ALS['geometry'] = USA_ALS.geometry.apply(lambda x: shapely.affinity.translate(x, xoff=0, yoff=-100))
35USA = USA[USA.STUSPS!='AK']
36New_USA = pd.concat([USA,USA_ALS])
37New_USA.geometry.plot()
38

1var data = google.visualization.arrayToDataTable(response.data.states);
2                var formatter = new google.visualization.NumberFormat({
3                    pattern: '$###,###.##'
4                });
5                formatter.format(data, 1);
6
7                var options = {
8                    region: 'US',
9                    displayMode: 'regions',
10                    resolution: 'provinces',
11                    colorAxis: {
12                        colors: ['#e6f4ff', '#008ffb', '#ff4560']
13                    },
14                    geochartVersion: 11,
15                    legend: {
16                        numberFormat: '$###,###.##'
17                    },
18                };
19
20                var chart = new google.visualization.GeoChart(document.getElementById(='kt_charts_states'));
21                chart.draw(data, options);
22[
23['State', 'Sales', 'Order Count'],
24['Alabama', 5939.95, 6],
25['Arizona', 5256.83, 9],
26['Arkansas', 7917.89, 14],
27['California', 24587.1, 37],
28['Colorado', 7494.87, 8],
29]
30r = (1 - point - start)/end * r1  +  (point-start)/end * r2
31g = (1 - point - start)/end * g1  +  (point-start)/end * g2
32b = (1 - point - start)/end * b1  +  (point-start)/end * b2
33
34where,
35rgb    - the color we want to find on the gradient
36r1g1b1 - starting color
37r2g2b2 - end color
38point  - sales value of the state
39start  - minimum sales: $80
40end    - maximum sales: $25,460.26
41

1var data = google.visualization.arrayToDataTable(response.data.states);
2                var formatter = new google.visualization.NumberFormat({
3                    pattern: '$###,###.##'
4                });
5                formatter.format(data, 1);
6
7                var options = {
8                    region: 'US',
9                    displayMode: 'regions',
10                    resolution: 'provinces',
11                    colorAxis: {
12                        colors: ['#e6f4ff', '#008ffb', '#ff4560']
13                    },
14                    geochartVersion: 11,
15                    legend: {
16                        numberFormat: '$###,###.##'
17                    },
18                };
19
20                var chart = new google.visualization.GeoChart(document.getElementById(='kt_charts_states'));
21                chart.draw(data, options);
22[
23['State', 'Sales', 'Order Count'],
24['Alabama', 5939.95, 6],
25['Arizona', 5256.83, 9],
26['Arkansas', 7917.89, 14],
27['California', 24587.1, 37],
28['Colorado', 7494.87, 8],
29]
30r = (1 - point - start)/end * r1  +  (point-start)/end * r2
31g = (1 - point - start)/end * g1  +  (point-start)/end * g2
32b = (1 - point - start)/end * b1  +  (point-start)/end * b2
33
34where,
35rgb    - the color we want to find on the gradient
36r1g1b1 - starting color
37r2g2b2 - end color
38point  - sales value of the state
39start  - minimum sales: $80
40end    - maximum sales: $25,460.26
41let info = [
42  ['State', 'Sales', 'Order Count'],
43  ['Alabama', 1939.95, 6],
44  ['Arizona', 5256.83, 9],
45  ['Arkansas', 7917.89, 14],
46  ['California', 20587.1, 32],
47  ['Colorado', 7494.87, 8],
48  ['Idaho', 80, 1],
49  ['Missouri', 25460.26, 40],
50  ['Texas', 13000, 20],
51];
52
53let gradient = ['#e6f4ff', '#008ffb', '#ff4560'];
54let range = {
55  start: 80,
56  end: 25460.26
57};
58
59google.charts.load('current', {
60  'packages': ['geochart'],
61  // Note: Because this chart requires geocoding, you'll need mapsApiKey.
62  // See: https://developers.google.com/chart/interactive/docs/basic_load_libs#load-settings
63  'mapsApiKey': 'AIzaSyD-9tSrke72PouQMnMX-a7eZSW0jkFMBWY'
64});
65google.charts.setOnLoadCallback(drawRegionsMap);
66
67function drawRegionsMap() {
68  var data = google.visualization.arrayToDataTable(info);
69  var formatter = new google.visualization.NumberFormat({
70    pattern: '$###,###.##'
71  });
72  formatter.format(data, 1);
73  var options = {
74    region: 'US',
75    displayMode: 'regions',
76    resolution: 'provinces',
77    colorAxis: {
78      colors: gradient
79    },
80    geochartVersion: 11,
81    legend: {
82      numberFormat: '$###,###.##'
83    },
84  };
85
86  var chart = new google.visualization.GeoChart(document.getElementById('kt_charts_states'));
87  chart.draw(data, options);
88};
89
90// display colors for each state
91let content = ''
92info.forEach((state, i) => {
93  if (i === 0) return;
94  content += `<div style='background-color: ${getStateColor(gradient, range, state[1])}'>${state[0]}</div>`;
95});
96stat.innerHTML = content;
97
98// interpolate colors
99function getStateColor(gradient, range, value) {
100  let colors = gradient.map(c => hexToRgb(c));
101  let sectionLength = (range.end - range.start) / (gradient.length - 1);
102  let section = (value / sectionLength) | 0;
103  if (section + 1 == gradient.length) section -= 1;
104
105  value = value - sectionLength * section - range.start;
106  let result = ['r', 'g', 'b'].map(c => {
107    // interpolate color from start color to end color
108    let out = (1 - (value / sectionLength)) * colors[section][c];
109    out += (value / sectionLength) * colors[section + 1][c];
110    return Math.ceil(out);
111  });
112  return rgbToHex(...result);
113}
114
115// utility functions
116function hexToRgb(hex) {
117  var shorthandRegex = /^#?([a-f\d])([a-f\d])([a-f\d])$/i;
118  hex = hex.replace(shorthandRegex, function(m, r, g, b) {
119    return r + r + g + g + b + b;
120  });
121
122  var result = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(hex);
123  return result ? {
124    r: parseInt(result[1], 16),
125    g: parseInt(result[2], 16),
126    b: parseInt(result[3], 16)
127  } : null;
128}
129
130function rgbToHex(r, g, b) {
131  return "#" + ((1 << 24) + ((r | 0) << 16) + ((g | 0) << 8) + (b | 0)).toString(16).slice(1);
132}

1var data = google.visualization.arrayToDataTable(response.data.states);
2                var formatter = new google.visualization.NumberFormat({
3                    pattern: '$###,###.##'
4                });
5                formatter.format(data, 1);
6
7                var options = {
8                    region: 'US',
9                    displayMode: 'regions',
10                    resolution: 'provinces',
11                    colorAxis: {
12                        colors: ['#e6f4ff', '#008ffb', '#ff4560']
13                    },
14                    geochartVersion: 11,
15                    legend: {
16                        numberFormat: '$###,###.##'
17                    },
18                };
19
20                var chart = new google.visualization.GeoChart(document.getElementById(='kt_charts_states'));
21                chart.draw(data, options);
22[
23['State', 'Sales', 'Order Count'],
24['Alabama', 5939.95, 6],
25['Arizona', 5256.83, 9],
26['Arkansas', 7917.89, 14],
27['California', 24587.1, 37],
28['Colorado', 7494.87, 8],
29]
30r = (1 - point - start)/end * r1  +  (point-start)/end * r2
31g = (1 - point - start)/end * g1  +  (point-start)/end * g2
32b = (1 - point - start)/end * b1  +  (point-start)/end * b2
33
34where,
35rgb    - the color we want to find on the gradient
36r1g1b1 - starting color
37r2g2b2 - end color
38point  - sales value of the state
39start  - minimum sales: $80
40end    - maximum sales: $25,460.26
41let info = [
42  ['State', 'Sales', 'Order Count'],
43  ['Alabama', 1939.95, 6],
44  ['Arizona', 5256.83, 9],
45  ['Arkansas', 7917.89, 14],
46  ['California', 20587.1, 32],
47  ['Colorado', 7494.87, 8],
48  ['Idaho', 80, 1],
49  ['Missouri', 25460.26, 40],
50  ['Texas', 13000, 20],
51];
52
53let gradient = ['#e6f4ff', '#008ffb', '#ff4560'];
54let range = {
55  start: 80,
56  end: 25460.26
57};
58
59google.charts.load('current', {
60  'packages': ['geochart'],
61  // Note: Because this chart requires geocoding, you'll need mapsApiKey.
62  // See: https://developers.google.com/chart/interactive/docs/basic_load_libs#load-settings
63  'mapsApiKey': 'AIzaSyD-9tSrke72PouQMnMX-a7eZSW0jkFMBWY'
64});
65google.charts.setOnLoadCallback(drawRegionsMap);
66
67function drawRegionsMap() {
68  var data = google.visualization.arrayToDataTable(info);
69  var formatter = new google.visualization.NumberFormat({
70    pattern: '$###,###.##'
71  });
72  formatter.format(data, 1);
73  var options = {
74    region: 'US',
75    displayMode: 'regions',
76    resolution: 'provinces',
77    colorAxis: {
78      colors: gradient
79    },
80    geochartVersion: 11,
81    legend: {
82      numberFormat: '$###,###.##'
83    },
84  };
85
86  var chart = new google.visualization.GeoChart(document.getElementById('kt_charts_states'));
87  chart.draw(data, options);
88};
89
90// display colors for each state
91let content = ''
92info.forEach((state, i) => {
93  if (i === 0) return;
94  content += `<div style='background-color: ${getStateColor(gradient, range, state[1])}'>${state[0]}</div>`;
95});
96stat.innerHTML = content;
97
98// interpolate colors
99function getStateColor(gradient, range, value) {
100  let colors = gradient.map(c => hexToRgb(c));
101  let sectionLength = (range.end - range.start) / (gradient.length - 1);
102  let section = (value / sectionLength) | 0;
103  if (section + 1 == gradient.length) section -= 1;
104
105  value = value - sectionLength * section - range.start;
106  let result = ['r', 'g', 'b'].map(c => {
107    // interpolate color from start color to end color
108    let out = (1 - (value / sectionLength)) * colors[section][c];
109    out += (value / sectionLength) * colors[section + 1][c];
110    return Math.ceil(out);
111  });
112  return rgbToHex(...result);
113}
114
115// utility functions
116function hexToRgb(hex) {
117  var shorthandRegex = /^#?([a-f\d])([a-f\d])([a-f\d])$/i;
118  hex = hex.replace(shorthandRegex, function(m, r, g, b) {
119    return r + r + g + g + b + b;
120  });
121
122  var result = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(hex);
123  return result ? {
124    r: parseInt(result[1], 16),
125    g: parseInt(result[2], 16),
126    b: parseInt(result[3], 16)
127  } : null;
128}
129
130function rgbToHex(r, g, b) {
131  return "#" + ((1 << 24) + ((r | 0) << 16) + ((g | 0) << 8) + (b | 0)).toString(16).slice(1);
132}#kt_charts_states{
133   width: 95vw;
134   height:92vh;
135}
136
137#stat {
138  position: fixed;
139  top: .5rem;
140  right: 1rem;
141}
142#stat div{
143  width: 100px
144}

1var data = google.visualization.arrayToDataTable(response.data.states);
2                var formatter = new google.visualization.NumberFormat({
3                    pattern: '$###,###.##'
4                });
5                formatter.format(data, 1);
6
7                var options = {
8                    region: 'US',
9                    displayMode: 'regions',
10                    resolution: 'provinces',
11                    colorAxis: {
12                        colors: ['#e6f4ff', '#008ffb', '#ff4560']
13                    },
14                    geochartVersion: 11,
15                    legend: {
16                        numberFormat: '$###,###.##'
17                    },
18                };
19
20                var chart = new google.visualization.GeoChart(document.getElementById(='kt_charts_states'));
21                chart.draw(data, options);
22[
23['State', 'Sales', 'Order Count'],
24['Alabama', 5939.95, 6],
25['Arizona', 5256.83, 9],
26['Arkansas', 7917.89, 14],
27['California', 24587.1, 37],
28['Colorado', 7494.87, 8],
29]
30r = (1 - point - start)/end * r1  +  (point-start)/end * r2
31g = (1 - point - start)/end * g1  +  (point-start)/end * g2
32b = (1 - point - start)/end * b1  +  (point-start)/end * b2
33
34where,
35rgb    - the color we want to find on the gradient
36r1g1b1 - starting color
37r2g2b2 - end color
38point  - sales value of the state
39start  - minimum sales: $80
40end    - maximum sales: $25,460.26
41let info = [
42  ['State', 'Sales', 'Order Count'],
43  ['Alabama', 1939.95, 6],
44  ['Arizona', 5256.83, 9],
45  ['Arkansas', 7917.89, 14],
46  ['California', 20587.1, 32],
47  ['Colorado', 7494.87, 8],
48  ['Idaho', 80, 1],
49  ['Missouri', 25460.26, 40],
50  ['Texas', 13000, 20],
51];
52
53let gradient = ['#e6f4ff', '#008ffb', '#ff4560'];
54let range = {
55  start: 80,
56  end: 25460.26
57};
58
59google.charts.load('current', {
60  'packages': ['geochart'],
61  // Note: Because this chart requires geocoding, you'll need mapsApiKey.
62  // See: https://developers.google.com/chart/interactive/docs/basic_load_libs#load-settings
63  'mapsApiKey': 'AIzaSyD-9tSrke72PouQMnMX-a7eZSW0jkFMBWY'
64});
65google.charts.setOnLoadCallback(drawRegionsMap);
66
67function drawRegionsMap() {
68  var data = google.visualization.arrayToDataTable(info);
69  var formatter = new google.visualization.NumberFormat({
70    pattern: '$###,###.##'
71  });
72  formatter.format(data, 1);
73  var options = {
74    region: 'US',
75    displayMode: 'regions',
76    resolution: 'provinces',
77    colorAxis: {
78      colors: gradient
79    },
80    geochartVersion: 11,
81    legend: {
82      numberFormat: '$###,###.##'
83    },
84  };
85
86  var chart = new google.visualization.GeoChart(document.getElementById('kt_charts_states'));
87  chart.draw(data, options);
88};
89
90// display colors for each state
91let content = ''
92info.forEach((state, i) => {
93  if (i === 0) return;
94  content += `<div style='background-color: ${getStateColor(gradient, range, state[1])}'>${state[0]}</div>`;
95});
96stat.innerHTML = content;
97
98// interpolate colors
99function getStateColor(gradient, range, value) {
100  let colors = gradient.map(c => hexToRgb(c));
101  let sectionLength = (range.end - range.start) / (gradient.length - 1);
102  let section = (value / sectionLength) | 0;
103  if (section + 1 == gradient.length) section -= 1;
104
105  value = value - sectionLength * section - range.start;
106  let result = ['r', 'g', 'b'].map(c => {
107    // interpolate color from start color to end color
108    let out = (1 - (value / sectionLength)) * colors[section][c];
109    out += (value / sectionLength) * colors[section + 1][c];
110    return Math.ceil(out);
111  });
112  return rgbToHex(...result);
113}
114
115// utility functions
116function hexToRgb(hex) {
117  var shorthandRegex = /^#?([a-f\d])([a-f\d])([a-f\d])$/i;
118  hex = hex.replace(shorthandRegex, function(m, r, g, b) {
119    return r + r + g + g + b + b;
120  });
121
122  var result = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(hex);
123  return result ? {
124    r: parseInt(result[1], 16),
125    g: parseInt(result[2], 16),
126    b: parseInt(result[3], 16)
127  } : null;
128}
129
130function rgbToHex(r, g, b) {
131  return "#" + ((1 << 24) + ((r | 0) << 16) + ((g | 0) << 8) + (b | 0)).toString(16).slice(1);
132}#kt_charts_states{
133   width: 95vw;
134   height:92vh;
135}
136
137#stat {
138  position: fixed;
139  top: .5rem;
140  right: 1rem;
141}
142#stat div{
143  width: 100px
144}<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
145<div id="kt_charts_states"></div>
146<div id="stat"></div>

1geo = {'type': 'Polygon',
2 'coordinates': [[[23.08437310100004, 53.15448536100007],
3   [23.08459767900007, 53.15448536100007],
4   [23.08594514600003, 53.153587050000056],
5   (...)
6   [23.08437310100004, 53.15448536100007]]]}
7[tuple(l) for l in geo['coordinates']]
8[([23.08437310100004, 53.15448536100007],
9  [23.08459767900007, 53.15448536100007],
10  (...)
11  [23.08437310100004, 53.15448536100007])]
12([(23.08437310100004, 53.15448536100007),
13  (23.08459767900007, 53.15448536100007),
14  (...)
15  (23.08437310100004, 53.15448536100007)])
16from itertools import chain
17
18
19geom = {...}
20polygon = Polygon(list(chain(*geom['coordinates']))
21

1<?php
2      $url = file_get_contents("libs/json/countryBorders.geo.json");
3      $arr = json_decode($url,true);
4    
5    
6      foreach($arr as $value)  {
7             echo $value['features'][0]['properties']['name'];
8             echo $value['features'][0]['properties']['iso_a2'];
9       };
10        
11?>
12{
13   "type":"FeatureCollection",
14   "features":[
15      {
16         "type":"Feature",
17         "properties":{
18            "name":"Bahamas",
19            "iso_a2":"BS",
20            "iso_a3":"BHS",
21            "iso_n3":"044"
22         },
23         "geometry":{
24            "type":"MultiPolygon",
25            "coordinates":[
26               [
27                  [
28                     [
29                        -77.53466,
30                        23.75975
31                     ],
32                     [
33                        -77.78,
34                        23.71
35                     ],
36                     [
37                        -78.03405,
38                        24.28615
39                     ],
40                     [
41                        -78.40848,
42                        24.57564
43                     ],
44                     [
45                        -78.19087,
46                        25.2103
47                     ],
48                     [
49                        -77.89,
50                        25.17
51                     ],
52                     [
53                        -77.54,
54                        24.34
55                     ],
56                     [
57                        -77.53466,
58                        23.75975
59                     ]
60                  ]
61               ],
62               [
63                  [
64                     [
65                        -77.82,
66                        26.58
67                     ],
68                     [
69                        -78.91,
70                        26.42
71                     ],
72                     [
73                        -78.98,
74                        26.79
75                     ],
76                     [
77                        -78.51,
78                        26.87
79                     ],
80                     [
81                        -77.85,
82                        26.84
83                     ],
84                     [
85                        -77.82,
86                        26.58
87                     ]
88                  ]
89               ],
90               [
91                  [
92                     [
93                        -77,
94                        26.59
95                     ],
96                     [
97                        -77.17255,
98                        25.87918
99                     ],
100                     [
101                        -77.35641,
102                        26.00735
103                     ],
104                     [
105                        -77.34,
106                        26.53
107                     ],
108                     [
109                        -77.78802,
110                        26.92516
111                     ],
112                     [
113                        -77.79,
114                        27.04
115                     ],
116                     [
117                        -77,
118                        26.59
119                     ]
120                  ]
121               ]
122            ]
123         }
124      }
125$url = file_get_contents("libs/json/countryBorders.geo.json");
126$arr = json_decode($url, true);
127    
128foreach($arr as $value)  {
129    foreach($value['features'] as $feature) {
130        echo $feature['properties']['name'];
131        echo $feature['properties']['iso_a2'];
132    }
133}
134

1const MEDIA_TYPES: Record<string, string> = {
2  ".md": "text/markdown",
3  ".html": "text/html",
4  ".htm": "text/html",
5  ".json": "application/json",
6  ".map": "application/json",
7  ".txt": "text/plain",
8  ".ts": "text/typescript",
9  ".tsx": "text/tsx",
10  ".js": "application/javascript",
11  ".jsx": "text/jsx",
12  ".gz": "application/gzip",
13  ".css": "text/css",
14  ".wasm": "application/wasm",
15  ".mjs": "application/javascript",
16  ".otf": "font/otf",
17  ".ttf": "font/ttf",
18  ".woff": "font/woff",
19  ".woff2": "font/woff2",
20  ".conf": "text/plain",
21  ".list": "text/plain",
22  ".log": "text/plain",
23  ".ini": "text/plain",
24  ".vtt": "text/vtt",
25  ".yaml": "text/yaml",
26  ".yml": "text/yaml",
27  ".mid": "audio/midi",
28  ".midi": "audio/midi",
29  ".mp3": "audio/mp3",
30  ".mp4a": "audio/mp4",
31  ".m4a": "audio/mp4",
32  ".ogg": "audio/ogg",
33  ".spx": "audio/ogg",
34  ".opus": "audio/ogg",
35  ".wav": "audio/wav",
36  ".webm": "audio/webm",
37  ".aac": "audio/x-aac",
38  ".flac": "audio/x-flac",
39  ".mp4": "video/mp4",
40  ".mp4v": "video/mp4",
41  ".mkv": "video/x-matroska",
42  ".mov": "video/quicktime",
43  ".svg": "image/svg+xml",
44  ".avif": "image/avif",
45  ".bmp": "image/bmp",
46  ".gif": "image/gif",
47  ".heic": "image/heic",
48  ".heif": "image/heif",
49  ".jpeg": "image/jpeg",
50  ".jpg": "image/jpeg",
51  ".png": "image/png",
52  ".tiff": "image/tiff",
53  ".psd": "image/vnd.adobe.photoshop",
54  ".ico": "image/vnd.microsoft.icon",
55  ".webp": "image/webp",
56  ".es": "application/ecmascript",
57  ".epub": "application/epub+zip",
58  ".jar": "application/java-archive",
59  ".war": "application/java-archive",
60  ".webmanifest": "application/manifest+json",
61  ".doc": "application/msword",
62  ".dot": "application/msword",
63  ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
64  ".dotx": "application/vnd.openxmlformats-officedocument.wordprocessingml.template",
65  ".cjs": "application/node",
66  ".bin": "application/octet-stream",
67  ".pkg": "application/octet-stream",
68  ".dump": "application/octet-stream",
69  ".exe": "application/octet-stream",
70  ".deploy": "application/octet-stream",
71  ".img": "application/octet-stream",
72  ".msi": "application/octet-stream",
73  ".pdf": "application/pdf",
74  ".pgp": "application/pgp-encrypted",
75  ".asc": "application/pgp-signature",
76  ".sig": "application/pgp-signature",
77  ".ai": "application/postscript",
78  ".eps": "application/postscript",
79  ".ps": "application/postscript",
80  ".rdf": "application/rdf+xml",
81  ".rss": "application/rss+xml",
82  ".rtf": "application/rtf",
83  ".apk": "application/vnd.android.package-archive",
84  ".key": "application/vnd.apple.keynote",
85  ".numbers": "application/vnd.apple.keynote",
86  ".pages": "application/vnd.apple.pages",
87  ".geo": "application/vnd.dynageo",
88  ".gdoc": "application/vnd.google-apps.document",
89  ".gslides": "application/vnd.google-apps.presentation",
90  ".gsheet": "application/vnd.google-apps.spreadsheet",
91  ".kml": "application/vnd.google-earth.kml+xml",
92  ".mkz": "application/vnd.google-earth.kmz",
93  ".icc": "application/vnd.iccprofile",
94  ".icm": "application/vnd.iccprofile",
95  ".xls": "application/vnd.ms-excel",
96  ".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
97  ".xlm": "application/vnd.ms-excel",
98  ".ppt": "application/vnd.ms-powerpoint",
99  ".pot": "application/vnd.ms-powerpoint",
100  ".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
101  ".potx": "application/vnd.openxmlformats-officedocument.presentationml.template",
102  ".xps": "application/vnd.ms-xpsdocument",
103  ".odc": "application/vnd.oasis.opendocument.chart",
104  ".odb": "application/vnd.oasis.opendocument.database",
105  ".odf": "application/vnd.oasis.opendocument.formula",
106  ".odg": "application/vnd.oasis.opendocument.graphics",
107  ".odp": "application/vnd.oasis.opendocument.presentation",
108  ".ods": "application/vnd.oasis.opendocument.spreadsheet",
109  ".odt": "application/vnd.oasis.opendocument.text",
110  ".rar": "application/vnd.rar",
111  ".unityweb": "application/vnd.unity",
112  ".dmg": "application/x-apple-diskimage",
113  ".bz": "application/x-bzip",
114  ".crx": "application/x-chrome-extension",
115  ".deb": "application/x-debian-package",
116  ".php": "application/x-httpd-php",
117  ".iso": "application/x-iso9660-image",
118  ".sh": "application/x-sh",
119  ".sql": "application/x-sql",
120  ".srt": "application/x-subrip",
121  ".xml": "application/xml",
122  ".zip": "application/zip",
123};
124
125/** Returns the content-type based on the extension of a path. */
126function contentType(pathname: string): string | undefined {
127  return MEDIA_TYPES[pathname];
128}
129
130console.log(contentType("/dashboard/v1/index.html"));
131console.log(contentType("/dashboard/v1/logo.svg"));
132/** Returns the content-type based on the extension of a path. */
133function contentType(ext: string): string | undefined {
134
135  const charsetUtf8 = "; charset=UTF-8";
136
137  // Content types that do not start with text/.. but usually contain charset=utf-8
138  const specialCase = [
139    "application/json",
140    "application/xml",
141    "application/rss+xml",
142  ];
143
144  let outputContentType = MEDIA_TYPES[ext];
145
146  // Return undefined.
147  if(!outputContentType) return;
148
149  if(outputContentType.startsWith("text/") || specialCase.includes(outputContentType)) {
150
151    // Combine Content-Type with charset=utf-8
152    outputContentType = outputContentType + charsetUtf8;
153
154  // Return combined.
155    return outputContentType;
156
157  } else {
158    // Return for any other types or undefined.
159    return outputContentType;
160  }
161  
162}
163

1const MEDIA_TYPES: Record<string, string> = {
2  ".md": "text/markdown",
3  ".html": "text/html",
4  ".htm": "text/html",
5  ".json": "application/json",
6  ".map": "application/json",
7  ".txt": "text/plain",
8  ".ts": "text/typescript",
9  ".tsx": "text/tsx",
10  ".js": "application/javascript",
11  ".jsx": "text/jsx",
12  ".gz": "application/gzip",
13  ".css": "text/css",
14  ".wasm": "application/wasm",
15  ".mjs": "application/javascript",
16  ".otf": "font/otf",
17  ".ttf": "font/ttf",
18  ".woff": "font/woff",
19  ".woff2": "font/woff2",
20  ".conf": "text/plain",
21  ".list": "text/plain",
22  ".log": "text/plain",
23  ".ini": "text/plain",
24  ".vtt": "text/vtt",
25  ".yaml": "text/yaml",
26  ".yml": "text/yaml",
27  ".mid": "audio/midi",
28  ".midi": "audio/midi",
29  ".mp3": "audio/mp3",
30  ".mp4a": "audio/mp4",
31  ".m4a": "audio/mp4",
32  ".ogg": "audio/ogg",
33  ".spx": "audio/ogg",
34  ".opus": "audio/ogg",
35  ".wav": "audio/wav",
36  ".webm": "audio/webm",
37  ".aac": "audio/x-aac",
38  ".flac": "audio/x-flac",
39  ".mp4": "video/mp4",
40  ".mp4v": "video/mp4",
41  ".mkv": "video/x-matroska",
42  ".mov": "video/quicktime",
43  ".svg": "image/svg+xml",
44  ".avif": "image/avif",
45  ".bmp": "image/bmp",
46  ".gif": "image/gif",
47  ".heic": "image/heic",
48  ".heif": "image/heif",
49  ".jpeg": "image/jpeg",
50  ".jpg": "image/jpeg",
51  ".png": "image/png",
52  ".tiff": "image/tiff",
53  ".psd": "image/vnd.adobe.photoshop",
54  ".ico": "image/vnd.microsoft.icon",
55  ".webp": "image/webp",
56  ".es": "application/ecmascript",
57  ".epub": "application/epub+zip",
58  ".jar": "application/java-archive",
59  ".war": "application/java-archive",
60  ".webmanifest": "application/manifest+json",
61  ".doc": "application/msword",
62  ".dot": "application/msword",
63  ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
64  ".dotx": "application/vnd.openxmlformats-officedocument.wordprocessingml.template",
65  ".cjs": "application/node",
66  ".bin": "application/octet-stream",
67  ".pkg": "application/octet-stream",
68  ".dump": "application/octet-stream",
69  ".exe": "application/octet-stream",
70  ".deploy": "application/octet-stream",
71  ".img": "application/octet-stream",
72  ".msi": "application/octet-stream",
73  ".pdf": "application/pdf",
74  ".pgp": "application/pgp-encrypted",
75  ".asc": "application/pgp-signature",
76  ".sig": "application/pgp-signature",
77  ".ai": "application/postscript",
78  ".eps": "application/postscript",
79  ".ps": "application/postscript",
80  ".rdf": "application/rdf+xml",
81  ".rss": "application/rss+xml",
82  ".rtf": "application/rtf",
83  ".apk": "application/vnd.android.package-archive",
84  ".key": "application/vnd.apple.keynote",
85  ".numbers": "application/vnd.apple.keynote",
86  ".pages": "application/vnd.apple.pages",
87  ".geo": "application/vnd.dynageo",
88  ".gdoc": "application/vnd.google-apps.document",
89  ".gslides": "application/vnd.google-apps.presentation",
90  ".gsheet": "application/vnd.google-apps.spreadsheet",
91  ".kml": "application/vnd.google-earth.kml+xml",
92  ".mkz": "application/vnd.google-earth.kmz",
93  ".icc": "application/vnd.iccprofile",
94  ".icm": "application/vnd.iccprofile",
95  ".xls": "application/vnd.ms-excel",
96  ".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
97  ".xlm": "application/vnd.ms-excel",
98  ".ppt": "application/vnd.ms-powerpoint",
99  ".pot": "application/vnd.ms-powerpoint",
100  ".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
101  ".potx": "application/vnd.openxmlformats-officedocument.presentationml.template",
102  ".xps": "application/vnd.ms-xpsdocument",
103  ".odc": "application/vnd.oasis.opendocument.chart",
104  ".odb": "application/vnd.oasis.opendocument.database",
105  ".odf": "application/vnd.oasis.opendocument.formula",
106  ".odg": "application/vnd.oasis.opendocument.graphics",
107  ".odp": "application/vnd.oasis.opendocument.presentation",
108  ".ods": "application/vnd.oasis.opendocument.spreadsheet",
109  ".odt": "application/vnd.oasis.opendocument.text",
110  ".rar": "application/vnd.rar",
111  ".unityweb": "application/vnd.unity",
112  ".dmg": "application/x-apple-diskimage",
113  ".bz": "application/x-bzip",
114  ".crx": "application/x-chrome-extension",
115  ".deb": "application/x-debian-package",
116  ".php": "application/x-httpd-php",
117  ".iso": "application/x-iso9660-image",
118  ".sh": "application/x-sh",
119  ".sql": "application/x-sql",
120  ".srt": "application/x-subrip",
121  ".xml": "application/xml",
122  ".zip": "application/zip",
123};
124
125/** Returns the content-type based on the extension of a path. */
126function contentType(pathname: string): string | undefined {
127  return MEDIA_TYPES[pathname];
128}
129
130console.log(contentType("/dashboard/v1/index.html"));
131console.log(contentType("/dashboard/v1/logo.svg"));
132/** Returns the content-type based on the extension of a path. */
133function contentType(ext: string): string | undefined {
134
135  const charsetUtf8 = "; charset=UTF-8";
136
137  // Content types that do not start with text/.. but usually contain charset=utf-8
138  const specialCase = [
139    "application/json",
140    "application/xml",
141    "application/rss+xml",
142  ];
143
144  let outputContentType = MEDIA_TYPES[ext];
145
146  // Return undefined.
147  if(!outputContentType) return;
148
149  if(outputContentType.startsWith("text/") || specialCase.includes(outputContentType)) {
150
151    // Combine Content-Type with charset=utf-8
152    outputContentType = outputContentType + charsetUtf8;
153
154  // Return combined.
155    return outputContentType;
156
157  } else {
158    // Return for any other types or undefined.
159    return outputContentType;
160  }
161  
162}
163let requestedFilePath = path.join("./", context.main.http.server.root, urlPathNameParsed.dir, urlPathNameParsed.base);
164
165try {
166  // try as file...
167  const file = await Deno.readFile(requestedFilePath);
168
169  // If file extension is not on media list...
170  if(typeof(contentType(urlPathNameParsed.ext)) === 'undefined') { 
171
172    // Set Content-Type header for this response
173    responseHeaders.set('Content-Type', 'text/plain; charset=UTF-8');
174
175    await e.respondWith(
176      new Response("HTTP 422: Unprocessable Entity", {
177        headers: responseHeaders,
178        status: 422,
179        statusText: 'Unprocessable Entity',
180      })
181    );
182
183  } else {
184
185    // Set Content-Type header for this response
186    responseHeaders.set('Content-Type', `${contentType(urlPathNameParsed.ext)}`);
187
188    // Build and send the response
189    await e.respondWith(
190      new Response(file, {
191        headers: responseHeaders, 
192        status: 200, 
193        statusText: 'OK'
194      })
195    );
196
197  }
198

1import pandas as pd
2
3df1 = pd.DataFrame({
4                    'City': ['San Francisco, CA','Oakland, CA'], 
5                    'Val': [1,2]
6                  })
7
8df2 = pd.DataFrame({
9                    'City': ['San Francisco-Oakland, CA','Salinas, CA'], 
10                    'Geo': ['geo1','geo2']
11                  })
12 City                   Val   Geo
13
14 San Francisco, CA      1     geo1
15 Oakland, CA            2     geo1
16import pandas as pd
17import numpy as np
18
19from thefuzz import process
20
21def fuzzy_match(
22    a: pd.DataFrame, b: pd.DataFrame, col: str, limit: int = 5, thresh: int = 80
23):
24    """use fuzzy matching to join on column"""
25
26    s = b[col].tolist()
27
28    matches = a[col].apply(lambda x: process.extract(x, s, limit=limit))
29    matches = pd.DataFrame(np.concatenate(matches), columns=["match", "score"])
30
31    # join other columns in b to matches
32    to_join = (
33        pd.merge(left=b, right=matches, how="right", left_on="City", right_on="match")
34        .set_index(  # create an index that represents the matching row in df a, you can drop this when `limit=1`
35            np.array(
36                list(
37                    np.repeat(i, limit if limit < len(b) else len(b))
38                    for i in range(len(a))
39                )
40            ).flatten()
41        )
42        .drop(columns=["match"])
43        .astype({"score": "int16"})
44    )
45    print(f"\t the index here represents the row in dataframe a on which to join")
46    print(to_join)
47
48    res = pd.merge(
49        left=a, right=to_join, left_index=True, right_index=True, suffixes=("", "_b")
50    )
51
52    # return only the highest match or you can just set the limit to 1
53    # and remove this
54    df = res.reset_index()
55    df = df.iloc[df.groupby(by="index")["score"].idxmax()].reset_index(drop=True)
56
57    return df.drop(columns=["City_b", "score", "index"])
58
59def test(df):
60
61    expected = pd.DataFrame(
62        {
63            "City": ["San Francisco, CA", "Oakland, CA"],
64            "Val": [1, 2],
65            "Geo": ["geo1", "geo1"],
66        }
67    )
68
69    print(f'{"expected":-^70}')
70    print(expected)
71
72    print(f'{"res":-^70}')
73    print(df)
74
75    assert expected.equals(df)
76
77
78if __name__ == "__main__":
79
80    a = pd.DataFrame({"City": ["San Francisco, CA", "Oakland, CA"], "Val": [1, 2]})
81    b = pd.DataFrame(
82        {"City": ["San Francisco-Oakland, CA", "Salinas, CA"], "Geo": ["geo1", "geo2"]}
83    )
84
85    print(f'\n\n{"fuzzy match":-^70}')
86    res = fuzzy_match(a, b, col="City")
87    test(res)
88
89

1geos.transform_point(us_bbox[0][0] + x, us_bbox[0][1] + y, ccrs.PlateCarree()) / sat_h
2grid_width = 500
3grid_height = 500
4grid = np.zeros((grid_width, grid_height))
5
6for x in range(0, grid_width):
7  for y in range(0, grid_height):
8    location_geos = geos.transform_point(us_bbox[0][0] + x, us_bbox[0][1] + y, ccrs.PlateCarree()) / sat_h
9    if not np.any(np.isnan(location_geos)):
10      grid[(x, y)] = C['BCM'].sel(y=location_geos[1],x=location_geos[0],method='nearest').values
11location_geos = geos.transform_point(us_bbox[0][0] + x, us_bbox[0][1] + y, ccrs.PlateCarree()) / sat_h
12

1library(sf)
2#> Linking to GEOS 3.8.1, GDAL 3.2.1, PROJ 7.2.1
3
4cities <- st_sf(city = "London", geometry = st_sfc(st_point(c(-0.1276, 51.5072))), crs = 4326)
5
6cities
7#> Simple feature collection with 1 feature and 1 field
8#> Geometry type: POINT
9#> Dimension:     XY
10#> Bounding box:  xmin: -0.1276 ymin: 51.5072 xmax: -0.1276 ymax: 51.5072
11#> Geodetic CRS:  WGS 84
12#>     city                geometry
13#> 1 London POINT (-0.1276 51.5072)
14st_crs(cities)
15#> Coordinate Reference System:
16#>   User input: EPSG:4326 
17#>   wkt:
18#> GEOGCRS["WGS 84",
19#>     DATUM["World Geodetic System 1984",
20#>         ELLIPSOID["WGS 84",6378137,298.257223563,
21#>             LENGTHUNIT["metre",1]]],
22#>     PRIMEM["Greenwich",0,
23#>         ANGLEUNIT["degree",0.0174532925199433]],
24#>     CS[ellipsoidal,2],
25#>         AXIS["geodetic latitude (Lat)",north,
26#>             ORDER[1],
27#>             ANGLEUNIT["degree",0.0174532925199433]],
28#>         AXIS["geodetic longitude (Lon)",east,
29#>             ORDER[2],
30#>             ANGLEUNIT["degree",0.0174532925199433]],
31#>     USAGE[
32#>         SCOPE["Horizontal component of 3D system."],
33#>         AREA["World."],
34#>         BBOX[-90,-180,90,180]],
35#>     ID["EPSG",4326]]
36st_crs(st_transform(cities, crs = 32630))
37#> Coordinate Reference System:
38#>   User input: EPSG:32630 
39#>   wkt:
40#> PROJCRS["WGS 84 / UTM zone 30N",
41#>     BASEGEOGCRS["WGS 84",
42#>         DATUM["World Geodetic System 1984",
43#>             ELLIPSOID["WGS 84",6378137,298.257223563,
44#>                 LENGTHUNIT["metre",1]]],
45#>         PRIMEM["Greenwich",0,
46#>             ANGLEUNIT["degree",0.0174532925199433]],
47#>         ID["EPSG",4326]],
48#>     CONVERSION["UTM zone 30N",
49#>         METHOD["Transverse Mercator",
50#>             ID["EPSG",9807]],
51#>         PARAMETER["Latitude of natural origin",0,
52#>             ANGLEUNIT["degree",0.0174532925199433],
53#>             ID["EPSG",8801]],
54#>         PARAMETER["Longitude of natural origin",-3,
55#>             ANGLEUNIT["degree",0.0174532925199433],
56#>             ID["EPSG",8802]],
57#>         PARAMETER["Scale factor at natural origin",0.9996,
58#>             SCALEUNIT["unity",1],
59#>             ID["EPSG",8805]],
60#>         PARAMETER["False easting",500000,
61#>             LENGTHUNIT["metre",1],
62#>             ID["EPSG",8806]],
63#>         PARAMETER["False northing",0,
64#>             LENGTHUNIT["metre",1],
65#>             ID["EPSG",8807]]],
66#>     CS[Cartesian,2],
67#>         AXIS["(E)",east,
68#>             ORDER[1],
69#>             LENGTHUNIT["metre",1]],
70#>         AXIS["(N)",north,
71#>             ORDER[2],
72#>             LENGTHUNIT["metre",1]],
73#>     USAGE[
74#>         SCOPE["Engineering survey, topographic mapping."],
75#>         AREA["Between 6°W and 0°W, northern hemisphere between equator and 84°N, onshore and offshore. Algeria. Burkina Faso. Côte' Ivoire (Ivory Coast). Faroe Islands - offshore. France. Ghana. Gibraltar. Ireland - offshore Irish Sea. Mali. Mauritania. Morocco. Spain. United Kingdom (UK)."],
76#>         BBOX[0,-6,84,0]],
77#>     ID["EPSG",32630]]
78library(sf)
79
80nc_4267 <- read_sf(system.file("shape/nc.shp", package="sf"))
81nc_3857 <- st_transform(nc_4267, 3857)
82
83st_crs(nc_4267, parameters = TRUE)$units_gdal
84#> [1] "degree"
85st_crs(nc_3857, parameters = TRUE)$units_gdal
86#> [1] "metre"
87

1library(sf)
2#> Linking to GEOS 3.8.1, GDAL 3.2.1, PROJ 7.2.1
3
4cities <- st_sf(city = "London", geometry = st_sfc(st_point(c(-0.1276, 51.5072))), crs = 4326)
5
6cities
7#> Simple feature collection with 1 feature and 1 field
8#> Geometry type: POINT
9#> Dimension:     XY
10#> Bounding box:  xmin: -0.1276 ymin: 51.5072 xmax: -0.1276 ymax: 51.5072
11#> Geodetic CRS:  WGS 84
12#>     city                geometry
13#> 1 London POINT (-0.1276 51.5072)
14st_crs(cities)
15#> Coordinate Reference System:
16#>   User input: EPSG:4326 
17#>   wkt:
18#> GEOGCRS["WGS 84",
19#>     DATUM["World Geodetic System 1984",
20#>         ELLIPSOID["WGS 84",6378137,298.257223563,
21#>             LENGTHUNIT["metre",1]]],
22#>     PRIMEM["Greenwich",0,
23#>         ANGLEUNIT["degree",0.0174532925199433]],
24#>     CS[ellipsoidal,2],
25#>         AXIS["geodetic latitude (Lat)",north,
26#>             ORDER[1],
27#>             ANGLEUNIT["degree",0.0174532925199433]],
28#>         AXIS["geodetic longitude (Lon)",east,
29#>             ORDER[2],
30#>             ANGLEUNIT["degree",0.0174532925199433]],
31#>     USAGE[
32#>         SCOPE["Horizontal component of 3D system."],
33#>         AREA["World."],
34#>         BBOX[-90,-180,90,180]],
35#>     ID["EPSG",4326]]
36st_crs(st_transform(cities, crs = 32630))
37#> Coordinate Reference System:
38#>   User input: EPSG:32630 
39#>   wkt:
40#> PROJCRS["WGS 84 / UTM zone 30N",
41#>     BASEGEOGCRS["WGS 84",
42#>         DATUM["World Geodetic System 1984",
43#>             ELLIPSOID["WGS 84",6378137,298.257223563,
44#>                 LENGTHUNIT["metre",1]]],
45#>         PRIMEM["Greenwich",0,
46#>             ANGLEUNIT["degree",0.0174532925199433]],
47#>         ID["EPSG",4326]],
48#>     CONVERSION["UTM zone 30N",
49#>         METHOD["Transverse Mercator",
50#>             ID["EPSG",9807]],
51#>         PARAMETER["Latitude of natural origin",0,
52#>             ANGLEUNIT["degree",0.0174532925199433],
53#>             ID["EPSG",8801]],
54#>         PARAMETER["Longitude of natural origin",-3,
55#>             ANGLEUNIT["degree",0.0174532925199433],
56#>             ID["EPSG",8802]],
57#>         PARAMETER["Scale factor at natural origin",0.9996,
58#>             SCALEUNIT["unity",1],
59#>             ID["EPSG",8805]],
60#>         PARAMETER["False easting",500000,
61#>             LENGTHUNIT["metre",1],
62#>             ID["EPSG",8806]],
63#>         PARAMETER["False northing",0,
64#>             LENGTHUNIT["metre",1],
65#>             ID["EPSG",8807]]],
66#>     CS[Cartesian,2],
67#>         AXIS["(E)",east,
68#>             ORDER[1],
69#>             LENGTHUNIT["metre",1]],
70#>         AXIS["(N)",north,
71#>             ORDER[2],
72#>             LENGTHUNIT["metre",1]],
73#>     USAGE[
74#>         SCOPE["Engineering survey, topographic mapping."],
75#>         AREA["Between 6°W and 0°W, northern hemisphere between equator and 84°N, onshore and offshore. Algeria. Burkina Faso. Côte' Ivoire (Ivory Coast). Faroe Islands - offshore. France. Ghana. Gibraltar. Ireland - offshore Irish Sea. Mali. Mauritania. Morocco. Spain. United Kingdom (UK)."],
76#>         BBOX[0,-6,84,0]],
77#>     ID["EPSG",32630]]
78library(sf)
79
80nc_4267 <- read_sf(system.file("shape/nc.shp", package="sf"))
81nc_3857 <- st_transform(nc_4267, 3857)
82
83st_crs(nc_4267, parameters = TRUE)$units_gdal
84#> [1] "degree"
85st_crs(nc_3857, parameters = TRUE)$units_gdal
86#> [1] "metre"
87st_is_longlat(nc_4267)
88#> [1] TRUE
89st_is_longlat(nc_3857)
90#> [1] FALSE
91