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| # added by Anaconda3 2019.10 installer | |
| # >>> conda init >>> | |
| # !! Contents within this block are managed by 'conda init' !! | |
| __conda_setup="$(CONDA_REPORT_ERRORS=false '/Users/{...username...}/opt/anaconda3/bin/conda' shell.bash hook 2> /dev/null)" | |
| if [ $? -eq 0 ]; then | |
| \eval "$__conda_setup" | |
| else | |
| if [ -f "/Users/{...username...}/opt/anaconda3/etc/profile.d/conda.sh" ]; then | |
| . "/Users/{...username...}/opt/anaconda3/etc/profile.d/conda.sh" | |
| CONDA_CHANGEPS1=false conda activate base |
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| import pandas as pd | |
| from geopandas import GeoDataFrame | |
| from shapely.geometry import Point | |
| import fiona | |
| df = pd.read_csv('data.csv') | |
| geometry = [Point(xy) for xy in zip(df.x, df.y)] | |
| crs = {'init': 'epsg:2263'} #http://www.spatialreference.org/ref/epsg/2263/ | |
| geo_df = GeoDataFrame(df, crs=crs, geometry=geometry) |
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| from cartodb import CartoDBAPIKey, CartoDBException, FileImport | |
| from _secret_info import cartodb_domain, API_KEY | |
| cl = CartoDBAPIKey(API_KEY, cartodb_domain) | |
| fi = FileImport('nyctrees2015.csv', cl, create_vis='true', privacy='public') # Import csv file, set privacy as 'link' and create a default viz | |
| fi.run() #https://github.com/CartoDB/cartodb-python | |
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| import json | |
| inFileName = 'data/cartojsontest1.carto.json' | |
| ouFileName = 'data/cartojsontest1_change_zoom10.carto.json' | |
| newMapName = 'THIS IS A TEST10' | |
| zoomLevel = 12 | |
| lat = '40.7127' | |
| lng = '-75.0059' | |
| oldDatasetName = 'infogroup_bus_2012_is_mcdonalds' | |
| newDatasetName = 'infogroup_bus_2012_like_exxon' |
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| import json | |
| def oneTest(): | |
| return 'so' | |
| def openJSON(inFile): | |
| with open(inFile) as json_data: | |
| data = json.load(json_data) | |
| return data |
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| ALTER TABLE table_name ADD COLUMN torque_class INTEGER; | |
| UPDATE table_name SET torque_class = ROUND(((input_col - (SELECT MIN(input_col) FROM table_name)) / (( (SELECT MAX(input_col) FROM table_name) - (SELECT MIN(input_col) FROM table_name))) * 255)) |
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| import urllib2 | |
| import json | |
| import csv | |
| import pandas as pd | |
| import numpy as np | |
| import decimal | |
| D = decimal.Decimal | |
| url = "https://www.wework.com/locations/all" | |
| data = urllib2.urlopen(url).read() |
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| df['col'] = ((((df['col']-df['col'].min()) / (df['col'].max() - df['col'].min()))*255).round()).astype(int) |
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| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title>Map Title</title> | |
| <meta name="viewport" content="initial-scale=1.0, user-scalable=no" /> | |
| <meta http-equiv="content-type" content="text/html; charset=UTF-8"/> | |
| <link rel="shortcut icon" href="https://cartodb.com/assets/favicon.ico" /> | |
| <style> | |
| html, body, #map { | |
| height: 100%; |
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| ALTER TABLE tablename ADD COLUMN new_col TEXT | |
| UPDATE tablename SET new_col = to_char(old_col, '9,999,999') |
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