I am trying to create a web map which shows the locations of volcanoes. I am using the Folium library in Python, and designing it with HTML. I am also using data from a Pandas DataFrame. However, when I run my code, I get the following error:
Traceback (most recent call last):
File "webmap.py", line 20, in <module>
iframe = folium.IFrame(html=html % (name, name, str(elev)), width=200, height=100)
TypeError: not all arguments converted during string formatting
This is my code:
import folium
import pandas
data = pandas.read_csv("Volcanoes.txt")
latitudes = list(data["LAT"])
longitudes = list(data["LON"])
elevations = list(data["ELEV"])
names = list(data["NAME"])
html = """
Volcano name:<br>
%s<br>
Height: %s m
"""
map = folium.Map(location=[38.58, -99.09], zoom_start=6, tiles="Stamen Terrain")
fg = folium.FeatureGroup(name="My Map")
for lat, lon, elev, name in zip(latitudes, longitudes, elevations, names):
iframe = folium.IFrame(html=html %(name, name, str(elev)), width=200, height=100)
fg.add_child(folium.Marker(location=[lat, lon], popup=folium.Popup(iframe), icon=folium.Icon(color="green")))
map.add_child(fg)
map.save("Map1Advacned.html")
The Pandas DataFrame contains information about each volcano, including its location (latitude and longitude), elevation, and name, which I parsed into a Python array in the first bit of my code.
Does anyone know why this error occurs? Any help would be much appreciated. Thanks in advance!
My supplementary data is Singapore government weather station temperature data. I've manipulated it a to fit into your example
changed location and zoom params as Singapore is in a different place and much smaller ;-)
your core issue is the string substitution into html variable. I much prefer f-strings so have changed it to this and it works.
import folium
import pandas as pd
df = pd.DataFrame({'latitude': [1.3764, 1.256, 1.3337, 1.3135, 1.3399, 1.2799],
'longitude': [103.8492, 103.679, 103.7768, 103.9625, 103.8878, 103.8703],
'value': [32.3, 31.7, 32.2, 29.9, 32.1, 32.5],
'tooltip': ['32.3 Ang Mo Kio Avenue 5 August 09, 2020 at 01:00PM',
'31.7 Banyan Road August 09, 2020 at 01:00PM',
'32.2 Clementi Road August 09, 2020 at 01:00PM',
'29.9 East Coast Parkway August 09, 2020 at 01:00PM',
'32.1 Kim Chuan Road August 09, 2020 at 01:00PM',
'32.5 Marina Gardens Drive August 09, 2020 at 01:00PM']})
data = df.copy().rename({'latitude':"LAT",'longitude':"LON",'value':"ELEV",'tooltip':"NAME"}, axis=1)
latitudes = list(data["LAT"])
longitudes = list(data["LON"])
elevations = list(data["ELEV"])
names = list(data["NAME"])
def myhtml(name, elev):
return f"""
Volcano name:<br>
{name}<br>
Height: {elev} m
"""
map = folium.Map(location=[1.34, 103.82], zoom_start=12, tiles="Stamen Terrain")
fg = folium.FeatureGroup(name="My Map")
for lat, lon, elev, name in zip(latitudes, longitudes, elevations, names):
iframe = folium.IFrame(html=myhtml(name, elev), width=200, height=100)
fg.add_child(folium.Marker(location=[lat, lon], popup=folium.Popup(iframe), icon=folium.Icon(color="green")))
map.add_child(fg)
map.save("Map1Advacned.html")
Related
I am trying to create variables location; contract items; contract code; federal aid using regex on the following text:
PAGE 1
BID OPENING DATE 07/25/18 FROM 0.2 MILES WEST OF ICE HOUSE 07/26/18 CONTRACT NUMBER 03-2F1304 ROAD TO 0.015 MILES WEST OF CONTRACT CODE 'A '
LOCATION 03-ED-50-39.5/48.7 DIVISION HIGHWAY ROAD 44 CONTRACT ITEMS
INSTALL SANDTRAPS AND PULLOUTS FEDERAL AID ACNH-P050-(146)E
PAGE 1
BID OPENING DATE 07/25/18 IN EL DORADO COUNTY AT VARIOUS 07/26/18 CONTRACT NUMBER 03-2H6804 LOCATIONS ALONG ROUTES 49 AND 193 CONTRACT CODE 'C ' LOCATION 03-ED-0999-VAR 13 CONTRACT ITEMS
TREE REMOVAL FEDERAL AID NONE
PAGE 1
BID OPENING DATE 07/25/18 IN LOS ANGELES, INGLEWOOD AND 07/26/18 CONTRACT NUMBER 07-296304 CULVER CITY, FROM I-105 TO PORT CONTRACT CODE 'B '
LOCATION 07-LA-405-R21.5/26.3 ROAD UNDERCROSSING 55 CONTRACT ITEMS
ROADWAY SAFETY IMPROVEMENT FEDERAL AID ACIM-405-3(056)E
This text is from one word file; I'll be looping my code on multiple doc files. In the text above are three location; contract items; contract code; federal aid pairs. But when I use regex to create variables, only the first instance of each pair is included.
The code I have right now is:
# imports
import os
import pandas as pd
import re
import docx2txt
import textract
import antiword
all_bod = []
all_cn = []
all_location = []
all_fedaid = []
all_contractcode = []
all_contractitems = []
all_file = []
text = ' PAGE 1
BID OPENING DATE 07/25/18 FROM 0.2 MILES WEST OF ICE HOUSE 07/26/18 CONTRACT NUMBER 03-2F1304 ROAD TO 0.015 MILES WEST OF CONTRACT CODE 'A '
LOCATION 03-ED-50-39.5/48.7 DIVISION HIGHWAY ROAD 44 CONTRACT ITEMS
INSTALL SANDTRAPS AND PULLOUTS FEDERAL AID ACNH-P050-(146)E
PAGE 1
BID OPENING DATE 07/25/18 IN EL DORADO COUNTY AT VARIOUS 07/26/18 CONTRACT NUMBER 03-2H6804 LOCATIONS ALONG ROUTES 49 AND 193 CONTRACT CODE 'C ' LOCATION 03-ED-0999-VAR 13 CONTRACT ITEMS
TREE REMOVAL FEDERAL AID NONE
PAGE 1
BID OPENING DATE 07/25/18 IN LOS ANGELES, INGLEWOOD AND 07/26/18 CONTRACT NUMBER 07-296304 CULVER CITY, FROM I-105 TO PORT CONTRACT CODE 'B '
LOCATION 07-LA-405-R21.5/26.3 ROAD UNDERCROSSING 55 CONTRACT ITEMS
ROADWAY SAFETY IMPROVEMENT FEDERAL AID ACIM-405-3(056)E'
bod1 = re.search('BID OPENING DATE \s+ (\d+\/\d+\/\d+)', text)
bod2 = re.search('BID OPENING DATE\n\n(\d+\/\d+\/\d+)', text)
if not(bod1 is None):
bod = bod1.group(1)
elif not(bod2 is None):
bod = bod2.group(1)
else:
bod = 'NA'
all_bod.append(bod)
# creating contract number
cn1 = re.search('CONTRACT NUMBER\n+(.*)', text)
cn2 = re.search('CONTRACT NUMBER\s+(.........)', text)
if not(cn1 is None):
cn = cn1.group(1)
elif not(cn2 is None):
cn = cn2.group(1)
else:
cn = 'NA'
all_cn.append(cn)
# location
location1 = re.search('LOCATION \s+\S+', text)
location2 = re.search('LOCATION \n+\S+', text)
if not(location1 is None):
location = location1.group(0)
elif not(location2 is None):
location = location2.group(0)
else:
location = 'NA'
all_location.append(location)
# federal aid
fedaid = re.search('FEDERAL AID\s+\S+', text)
fedaid = fedaid.group(0)
all_fedaid.append(fedaid)
# contract code
contractcode = re.search('CONTRACT CODE\s+\S+', text)
contractcode = contractcode.group(0)
all_contractcode.append(contractcode)
# contract items
contractitems = re.search('\d+ CONTRACT ITEMS', text)
contractitems = contractitems.group(0)
all_contractitems.append(contractitems)
This code parses the only first instance of these variables in the text.
contract-number
location
contract-items
contract-code
federal-aid
03-2F1304
03-ED-50-39.5/48.7
44
A
ACNH-P050-(146)E
But, I am trying to figure out a way to get all possible instances in different observations.
contract-number
location
contract-items
contract-code
federal-aid
03-2F1304
03-ED-50-39.5/48.7
44
A
ACNH-P050-(146)E
03-2H6804
03-ED-0999-VAR
13
C
NONE
07-296304
07-LA-405-R21.5/26.3
55
B
ACIM-405-3(056)E
The all_variables in the code are for looping over multiple word files - we can ignore that if we want :).
Any leads would be super helpful. Thanks so much!
import re
data = []
df = pd.DataFrame()
regex_contract_number =r"(?:CONTRACT NUMBER\s+(?P<contract_number>\S+?)\s)"
regex_location = r"(?:LOCATION\s+(?P<location>\S+))"
regex_contract_items = r"(?:(?P<contract_items>\d+)\sCONTRACT ITEMS)"
regex_federal_aid =r"(?:FEDERAL AID\s+(?P<federal_aid>\S+?)\s)"
regex_contract_code =r"(?:CONTRACT CODE\s+\'(?P<contract_code>\S+?)\s)"
regexes = [regex_contract_number,regex_location,regex_contract_items,regex_federal_aid,regex_contract_code]
for regex in regexes:
for match in re.finditer(regex, text):
data.append(match.groupdict())
df = pd.concat([df, pd.DataFrame(data)], axis=1)
data = []
df
I have a dataframe containing names of Brazilian authors, their novels, the publishing year of these novels, the cities that were cited in them, and the geolocalisation of these cities.
I would like to display all this information on a map using folium.On the map, I would like to see the clusters of the cities mentioned in the novels and the year of publication of these books. The cluster will vary according to the publishing year of the novels.
The following code performs the first task (creating clusters with the mentioned cities and their geolocations), but does not perform the second.Even though I have manged to write on the top the ranging dates (novels from 1840 to 1860), the map does't not change according to them:
map3 = folium.Map(location=[-14.235004, -51.92528], zoom_start=5)
mcg = folium.plugins.MarkerCluster(control=False)
map3.add_child(mcg)
g1 = folium.plugins.FeatureGroupSubGroup(mcg, 'Romances (1840 - 1860)')
map3.add_child(g1)
g2 = folium.plugins.FeatureGroupSubGroup(mcg, 'Romances (1860 - 1880)')
map3.add_child(g2)
g3 = folium.plugins.FeatureGroupSubGroup(mcg, 'Romances (1880 - 1900)')
map3.add_child(g3)
for point in range(0, len(locationlist)):
popup = """
Cidade : <b>%s</b><br>
Autor : <b>%s</b><br>
Nome do romance : <b>%s</b><br>
Ano de publicação da obra : <b>%s</b><br>
""" % (res['ocorrências_match'][point], res['autor'][point], res['nome_do_romance'][point], res['ano_de_publicação'][point])
if v['ano_de_publicação'] in range(1840,1860):
folium.Marker(locationlist[point], tooltip=popup, icon=folium.Icon(color=res["color"][point], icon_color='white', angle=0, prefix='fa')).add_to(g1)
elif v['ano_de_publicação'] in range(1860,1880):
folium.Marker(locationlist[point], tooltip=popup, icon=folium.Icon(color=res["color"][point], icon_color='white', angle=0, prefix='fa')).add_to(g2)
elif v['ano_de_publicação'] in range(1880,1900):
folium.Marker(locationlist[point], tooltip=popup, icon=folium.Icon(color=res["color"][point], icon_color='white', angle=0, prefix='fa')).add_to(g3)
l = folium.LayerControl().add_to(map3)
map3
Output
How can I combine the MarkerCluster with the FeatureGroup at the same time?
I try to get the data from pyOWM package using city name but in some cases because of city typo error
not getting data & it breaks the process.
I want to get the weather data using lat-long but don't know how to set function for it.
Df1:
-----
User City State Zip Lat Long
-----------------------------------------------------------------------------
A Kuala Lumpur Wilayah Persekutuan 50100 5.3288907 103.1344397
B Dublin County Dublin NA 50.2030506 14.5509842
C Oconomowoc NA NA 53.3640384 -6.1953066
D Mumbai Maharashtra 400067 19.2177166 72.9708833
E Mratin Stredocesky kraj 250 63 40.7560585 -5.6924778
.
.
.
----------------------------------
Code:
--------
import time
from tqdm.notebook import tqdm
import pyowm
from pyowm.utils import config
from pyowm.utils import timestamps
cities = Df1["City"].unique().tolist()
cities1 = cities [:5]
owm = pyowm.OWM('bee8db7d50a4b777bfbb9f47d9beb7d0')
mgr = owm.weather_manager()
'''
Step-1 Define list where save the data
'''
list_wind_Speed =[]
list_tempreture =[]
list_max_temp =[]
list_min_temp =[]
list_humidity =[]
list_pressure =[]
list_city = []
list_cloud=[]
list_status =[]
list_rain =[]
'''
Step-2 Fetch data
'''
j=0
for city in tqdm(cities1):
j=+1
if j < 60:
# one_call_obs = owm.weather_at_coords(52.5244, 13.4105).weather
# one_call_obs.current.humidity
observation = mgr.weather_at_place(city)
l = observation.weather
list_city.append(city)
list_wind_Speed.append(l.wind()['speed'])
list_tempreture.append(l.temperature('celsius')['temp'])
list_max_temp.append(l.temperature('celsius')['temp_max'])
list_min_temp.append(l.temperature('celsius')['temp_min'])
list_humidity.append(l.humidity)
list_pressure.append(l.pressure['press'])
list_cloud.append(l.clouds)
list_rain.append(l.rain)
else:
time.sleep(60)
j=0
'''
Step-3 Blank data frame and store data in that
'''
df2 = pd.DataFrame()
df2["City"] = list_city
df2["Temp"] = list_tempreture
df2["Max_Temp"] = list_max_temp
df2["Min_Temp"] = list_min_temp
df2["Cloud"] = list_cloud
df2["Humidity"] = list_humidity
df2["Pressure"] = list_pressure
df2["Status"] = list_status
df2["Rain"] = list_status
df2
From the above code, I get the result as below,
City | Temp |Max_Temp|Min_Temp|Cloud |Humidity|Pressure |Status | Rain
------------------------------------------------------------------------------------------
Kuala Lumpur|29.22 |30.00 |27.78 | 20 |70 |1007 | moderate rain | moderate rain
Dublin |23.12 |26.43 |22.34 | 15 |89 | 978 | cloudy | cloudy
...
Now because of some city typo error processes getting stop,
Looking for an alternate solution of it and try to get weather data from Lat-Long but don't know how to set function for pass lat & long column data.
Df1 = {'User':['A','B','C','D','E'],
'City':['Kuala Lumpur','Dublin','Oconomowoc','Mumbai','Mratin'],
'State':['Wilayah Persekutuan','County Dublin',NA,1'Maharashtra','Stredocesky kraj'],
'Zip': [50100,NA,NA,400067,250 63],
'Lat':[5.3288907,50.2030506,53.3640384,19.2177166,40.7560585],
'Long':[103.1344397,14.5509842,-6.1953066,72.9708833,-5.6924778]}
# Try to use this code to get wather data
# one_call_obs = owm.weather_at_coords(52.5244, 13.4105).weather
# one_call_obs.current.humidity
Expected Result
--------------
User | City | Lat | Long | Temp | Cloud | Humidity | Pressure | Rain | Status
-----------------------------------------------------------------------------
Catch the error if a city is not found, parse the lat/lon from the dataframe. Use that lat/lon to create a bounding box and use weather_at_places_in_bbox to get a list of observations in that area.
import time
from tqdm.notebook import tqdm
import pyowm
from pyowm.utils import config
from pyowm.utils import timestamps
import pandas as pd
from pyowm.commons.exceptions import NotFoundError, ParseAPIResponseError
df1 = pd.DataFrame({'City': ('Kuala Lumpur', 'Dublin', 'Oconomowoc', 'Mumbai', 'C airo', 'Mratin'),
'Lat': ('5.3288907', '50.2030506', '53.3640384', '19.2177166', '30.22', '40.7560585'),
'Long': ('103.1344397', '14.5509842', '-6.1953066', '72.9708833', '31', '-5.6924778')})
cities = df1["City"].unique().tolist()
owm = pyowm.OWM('bee8db7d50a4b777bfbb9f47d9beb7d0')
mgr = owm.weather_manager()
for city in cities:
try:
observation = mgr.weather_at_place(city)
# print(city, observation)
except NotFoundError:
# get city by lat/lon
lat_top = float(df1.loc[df1['City'] == city, 'Lat'])
lon_left = float(df1.loc[df1['City'] == city, 'Long'])
lat_bottom = lat_top - 0.3
lon_right = lon_left + 0.3
try:
observations = mgr.weather_at_places_in_bbox(lon_left, lat_bottom, lon_right, lat_top, zoom=5)
observation = observations[0]
except ParseAPIResponseError:
raise RuntimeError(f"Couldn't find {city} at lat: {lat_top} / lon: {lon_right}, try tweaking the bounding box")
weather = observation.weather
temp = weather.temperature('celsius')['temp']
print(f"The current temperature in {city} is {temp}")
I want to run the following code. My goal is to produce a .csv dataframe from a netcdf file in which I have isolated variables. I also copied the print(my_file) below for you to see the structure of my netcdf file. The error occurs when I run pd.Series as shown below :
temp_ts = pd.Series(temp, index=dtime)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/gpfs/apps/miniconda3/lib/python3.7/site-packages/pandas/core/series.py", line 305, in __init__
data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
File "/gpfs/apps/miniconda3/lib/python3.7/site-packages/pandas/core/construction.py", line 482, in sanitize_array
raise Exception("Data must be 1-dimensional")
Exception: Data must be 1-dimensional
Below, all of my code :
#netcdf to .csv
import netCDF4
import pandas as pd
import numpy as np
temp_nc_file = '/gpfs/home/UDCPP/barrier_c/Test_NCO/temp_Corse_10m_201704.nc'
nc = netCDF4.Dataset(temp_nc_file, mode='r')
nc.variables.keys()
lat = nc.variables['latitude'][:]
lon = nc.variables['longitude'][:]
time_var = nc.variables['time']
dtime = netCDF4.num2date(time_var[:],time_var.units)
temp = nc.variables['TEMP'][:]
# a pandas.Series designed for time series of a 2D lat,lon grid
temp_ts = pd.Series(temp, index=dtime)
temp_ts.to_csv('temp.csv',index=True, header=True)
And finally the print(my_file) result if useful :
print(nc)
<class 'netCDF4._netCDF4.Dataset'>
root group (NETCDF4_CLASSIC data model, file format HDF5):
limi: 0
lima: 1100
pasi: 1
ljmi: 0
ljma: 462
pasj: 1
lkmi: 1
lkma: 60
pask: 1
global_imin: 0
global_imax: 1100
global_jmin: 0
global_jmax: 462
data_type: OCO oriented grid
format_version: 1.3.1
Conventions: CF-1.6 OCO-1.3.1 COMODO-1.0
netcdf_version: 4.1.2
product_version: 1.0
references: http://www.previmer.org/
easting: longitude
northing: latitude
grid_projection: n/a
distribution_statement: Data restrictions: for registered users only
institution: IFREMER
institution_references: http://www.ifremer.fr/
data_centre: IFREMER OCO DATA CENTER
data_centre_references: http://www.previmer.org/
title: PREVIMER MENOR 1200 forecast
creation_date: 2017-01-03T20:21:27Z
run_time: 2017-01-03T20:21:27Z
history: Tue Jun 9 18:24:38 2020: nces -O -d level,10,10 temp_Corse_201704.nc temp_Corse_10m_201704.nc
Tue Jun 9 15:41:33 2020: nces -O -d ni,565,700 -d nj,150,350 temp_201704.nc temp_Corse_201704.nc
Tue Jun 9 15:32:46 2020: ncks -O -v TEMP champs_meno_BE201704.nc temp_201704.nc
Mon Nov 6 10:27:14 2017: /appli/nco/nco-4.6.4__gcc-6.3.0/bin/ncrcat /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T0000Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T0300Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T0600Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T0900Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T1200Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T1500Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T1800Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170101T2100Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170102T0000Z.nc /home1/datawork/scoudray/DATARESU/MENOR/201701BE/MARC_F2-MARS3D-MENOR1200_20170102T0300Z.nc 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2017-01-03T20:21:27Z: creation
model_name: MARS
arakawa_grid_type: C1
source: MARS3D V10.10
area: North Western Mediterranean Sea
southernmost_latitude: 39.5000
northernmost_latitude: 44.5000
latitude_resolution: 1.082250000000000E-002
westernmost_longitude: 0.0000
easternmost_longitude: 15.9999
longitude_resolution: 1.454540000000000E-002
minimum_depth: 5.000000
maximum_depth: 3500.000
depth_resolution: n/a
forecast_range: 4-days forecast
forecast_type: forecast
operational_status: experimental
NCO: netCDF Operators version 4.9.3 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)
start_date: 2017-01-01T00:00:00Z
stop_date: 2017-01-01T00:00:00Z
software_version: PREVIMER forecasting system v2
product_name: PREVIMER_F2-MARS3D-MENOR1200_20170101T0000Z.nc
field_type: 3-hourly
comment: Use of Meteo-France ARPEGEHR meteorological data
contact: cdoco-exploit#ifremer.fr
quality_index: 0
nco_openmp_thread_number: 1
dimensions(sizes): nj(201), ni(136), time(248), level(1)
variables(dimensions): float32 H0(nj,ni), float32 TEMP(time,level,nj,ni), float32 XE(time,nj,ni), float32 b(), float32 hc(nj,ni), float64 latitude(nj,ni), float32 level(level), float64 longitude(nj,ni), float32 ni(ni), float32 nj(nj), float32 theta(), float64 time(time)
groups:
THANK YOU IN ADVANCE FOR YOUR HELP !
I'm not sure if this is what you are looking for but you could try this.
import xarray as xr
file = xr.open_dataset('/gpfs/home/UDCPP/barrier_c/Test_NCO/temp_Corse_10m_201704.nc')
temp_ts = file['TEMP'].to_series()
temp_ts.to_csv('temp.csv',index=True, header=True)
I am trying to create a webscraper for a website. The problem is that after the collected data is stored in a list, I'm not able to write this to a csv file properly. I have been stuck for ages with this problem and hopefully someone has an idea about how to fix this one!
The loop to get the data from the web pages:
import csv
from htmlrequest import simple_get
from htmlrequest import BeautifulSoup
# Define variables
listData = ['Companies', 'Locations', 'Descriptions']
plus = 15
max = 30
count = 0
# while loop to repeat process till max is reached
while (count <= max):
start = 'https://www.companiesintheuk.co.uk/find?q=Activities+of+sport+clubs&start=' + str(count) + '&s=h&t=SicCodeSearch&location=&sicCode=93120'
raw_html = simple_get(start)
soup = BeautifulSoup(raw_html, 'html.parser')
for i, div in enumerate(soup.find_all('div', class_="search_result_title")):
listData[0] = listData[0].strip() + div.text
for i, div2 in enumerate(soup.find_all('div', class_="searchAddress")):
listData[1] = listData[1].strip() + div2.text
# This is extra information
# for i, div3 in enumerate(soup.find_all('div', class_="searchSicCode")):
# listData[2] = listData[2].strip() + div3.text
count = count + plus
output example if printed:
Companies
(AMG) AGILITY MANAGEMENT GROUP LTD
(KLA) LIONS/LIONESS FOOTBALL TEAMS WORLD CUP LTD
(Dissolved)
1 SPORT ORGANISATION LIMITED
100UK LTD
1066 GYMNASTICS
1066 SPECIALS
10COACHING LIMITED
147 LOUNGE LTD
147 SNOOKER AND POOL CLUB (LEICESTER) LIMITED
Locations
ENGLAND, BH8 9PS
LONDON, EC2M 2PL
ENGLAND, LS7 3JB
ENGLAND, LE2 8FN
UNITED KINGDOM, N18 2QX
AVON, BS5 0JH
UNITED KINGDOM, WC2H 9JQ
UNITED KINGDOM, SE18 5SZ
UNITED KINGDOM, EC1V 2NX
I've tried to get it into a CSV file by using this code but I can't figure out how to properly format my output! Any suggestions are welcome.
# writing to csv
with open('test.csv', 'w') as csvfile:
write = csv.writer(csvfile, delimiter=',')
write.writerow(['Name','Location'])
write.writerow([listData[0],listData[1]])
print("Writing has been done!")
I want the code to be able to format it properly in the csv file to be able to import the two rows in a database.
This is the output when I write the data on 'test.csv'
which will result into this when opened up
The expected outcome would be something like this!
I'm not sure how it is improperly formatted, but maybe you just need to replace with open('test.csv', 'w') with with open('test.csv', 'w+', newline='')
I've combined your code (taking out htmlrequests for requests and bs4 modules and also not using listData, but instead creating my own lists. I've left your lists but they do nothing):
import csv
import bs4
import requests
# Define variables
listData = ['Companies', 'Locations', 'Descriptions']
company_list = []
locations_list = []
plus = 15
max = 30
count = 0
# while loop to repeat process till max is reached
while count <= max:
start = 'https://www.companiesintheuk.co.uk/find?q=Activities+of+sport+clubs&start={}&s=h&t=SicCodeSearch&location=&sicCode=93120'.format(count)
res = requests.get(start)
soup = bs4.BeautifulSoup(res.text, 'html.parser')
for i, div in enumerate(soup.find_all('div', class_="search_result_title")):
listData[0] = listData[0].strip() + div.text
company_list.append(div.text.strip())
for i, div2 in enumerate(soup.find_all('div', class_="searchAddress")):
listData[1] = listData[1].strip() + div2.text
locations_list.append(div2.text.strip())
# This is extra information
# for i, div3 in enumerate(soup.find_all('div', class_="searchSicCode")):
# listData[2] = listData[2].strip() + div3.text
count = count + plus
if len(company_list) == len(locations_list):
with open('test.csv', 'w+', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter=',')
writer.writerow(['Name', 'Location'])
for i in range(len(company_list)):
writer.writerow([company_list[i], locations_list[i]])
Which generates a csv file like:
Name,Location
(AMG) AGILITY MANAGEMENT GROUP LTD,"UNITED KINGDOM, M6 6DE"
"(KLA) LIONS/LIONESS FOOTBALL TEAMS WORLD CUP LTD
(Dissolved)","ENGLAND, BD1 2PX"
0161 STUDIOS LTD,"UNITED KINGDOM, HD6 3AX"
1 CLICK SPORTS MANAGEMENT LIMITED,"ENGLAND, E10 5PW"
1 SPORT ORGANISATION LIMITED,"UNITED KINGDOM, CR2 6NF"
100UK LTD,"UNITED KINGDOM, BN14 9EJ"
1066 GYMNASTICS,"EAST SUSSEX, BN21 4PT"
1066 SPECIALS,"EAST SUSSEX, TN40 1HE"
10COACHING LIMITED,"UNITED KINGDOM, SW6 6LR"
10IS ACADEMY LIMITED,"ENGLAND, PE15 9PS"
"10TH MAN LIMITED
(Dissolved)","GLASGOW, G3 6AN"
12 GAUGE EAST MANCHESTER COMMUNITY MMA LTD,"ENGLAND, OL9 8DQ"
121 MAKING WAVES LIMITED,"TYNE AND WEAR, NE30 1AR"
121 WAVES LTD,"TYNE AND WEAR, NE30 1AR"
1-2-KICK LTD,"ENGLAND, BH8 9PS"
"147 HAVANA LIMITED
(Liquidation)","LONDON, EC2M 2PL"
147 LOUNGE LTD,"ENGLAND, LS7 3JB"
147 SNOOKER AND POOL CLUB (LEICESTER) LIMITED,"ENGLAND, LE2 8FN"
1ACTIVE LTD,"UNITED KINGDOM, N18 2QX"
1ON1 KING LTD,"AVON, BS5 0JH"
1PUTT LTD,"UNITED KINGDOM, WC2H 9JQ"
1ST SPORTS LTD,"UNITED KINGDOM, SE18 5SZ"
2 BRO PRO EVENTS LTD,"UNITED KINGDOM, EC1V 2NX"
2 SPLASH SWIM SCHOOL LTD,"ENGLAND, B36 0EY"
2 STEPPERS C.I.C.,"SURREY, CR0 6BX"
2017 MOTO LIMITED,"UNITED KINGDOM, ME2 4NW"
2020 ARCHERY LTD,"LONDON, SE16 6SS"
21 LEISURE LIMITED,"LONDON, EC4M 7WS"
261 FEARLESS CLUB UNITED KINGDOM CIC,"LANCASHIRE, LA2 8RF"
2AIM4 LIMITED,"HERTFORDSHIRE, SG2 0JD"
2POINT4 FM LTD,"LONDON, NW10 8LW"
3 LIONS SCHOOL OF SPORT LTD,"BRISTOL, BS20 8BU"
3 PT LTD,"ANTRIM, BT40 2FB"
3 PUTT LIFE LTD,"UNITED KINGDOM, LU3 2DP"
3 THIRTY SEVEN LTD,"KENT, DA9 9RS"
3:30 SOCCER SCHOOL LTD,"UNITED KINGDOM, EH6 7JB"
30 MINUTE WORKOUT (LLANISHEN) LTD,"PONTYCLUN, CF72 9UA"
321 RELAX LTD,"MID GLAMORGAN, CF83 3HL"
360 MOTOR RACING CLUB LTD,"HALSTEAD, CO9 2ET"
3LIONSATHLETICS LIMITED,"ENGLAND, S3 8DB"
3S SWIM ROMFORD LTD,"UNITED KINGDOM, DA9 9DR"
3XL EVENT MANAGEMENT LIMITED,"KENT, BR3 4NW"
3XL MOTORSPORT MANAGEMENT LIMITED,"KENT, BR3 4NW"
4 CORNER FOOTBALL LTD,"BROMLEY, BR1 5DD"
4 PRO LTD,"UNITED KINGDOM, FY5 5HT"
Which seems fine to me, but your post was very unclear about how you expected it to be formatted so I really have no idea