def _plot_map(results,
figsize=(15, 8),
cmap=['#ff0000'],
showfig=True,
verbose=3):
out = None
if (results['method'] == 'geo') and (not results['df'].empty):
# get map name
map_name = worldmap.code2county(results['geo'])[1]
# Normalize
data, colnames, idx_names = _normalize_data(results['df'])
# Plot per searchword
for i in range(0, data.shape[1]):
# Color only those with value>0
idx = np.where(data[:, i] > 0)[0]
# county_names = results['df'].iloc[idx,i].index.values
county_names = idx_names[idx]
opacity = data[idx, i]
filename = map_name + '_' + colnames[i] + '.svg'
# If no data, set all on black
if len(county_names) == 0:
county_names = idx_names
opacity = 1
cmap = ['#D3D3D3']
# Plot on map
out = worldmap.plot(county_names,
map_name=map_name,
opacity=opacity,
cmap=cmap,
filename=filename,
showfig=showfig)
return out
def _spatio_per_searchword(searchwords,
geo='',
date_start=None,
date_stop=None,
method='news',
include_suggestions=False,
verbose=3):
if geo == '':
raise Exception('geo should be a string')
if isinstance(geo, list):
raise Exception('geo should be a string and can not be of type list.')
if isinstance(searchwords, str):
searchwords = [searchwords]
# Get data range and message
_, _, date_range = _set_dates(date_start, date_stop, verbose=verbose)
# Collect data per searchword
df_city = []
for searchword in searchwords:
if verbose >= 3:
print('[googletrends] [%s] Working on %s..' % (geo, searchword))
data_per_city = _country_per_searchword(
[searchword],
geo=geo,
date_start=date_start,
date_stop=date_stop,
method=method,
include_suggestions=include_suggestions,
verbose=0)
df_city.append(pd.DataFrame(data_per_city))
# Combine data in 1 dataframe
df_city = pd.concat(df_city, axis=1)
# Fin
out = {}
out['method'] = 'geo'
out['df'] = df_city
out['geo'] = geo
out['geo_names'] = worldmap.code2county(geo)[1]
out['date_range'] = date_range
out['searchwords'] = searchwords
return (out)
# %%
import worldmap
print(worldmap.__version__)
# %% Retrieve availble maps that can be used to superimpose data on top of it
[map_names, filenames] = worldmap.map_names()
# %% Retrieve names in map
county_names = worldmap.county_names(map_name='world')
county_names = worldmap.county_names(map_name='netherlands')
county_names = worldmap.county_names(map_name='belgium')
county_names = worldmap.county_names(map_name='new zealand')
# %% Retrieve citynames for abbrevations
out = worldmap.code2county('NL')
out = worldmap.code2county('GB')
# %% Retrieve abbrevations for city names
out = worldmap.county2code('Netherlands')
out = worldmap.county2code('Germany')
# %% Coloring of maps
county_names = ['zeeland', 'Overijssel', 'flevoland']
opacity = [0.4, 0.6, 0.9]
out = worldmap.plot(county_names,
opacity=opacity,
cmap='Set1',
map_name='netherlands',
filename='Netherlands_map.svg')
county_names = ['Norway', 'Nederland', 'belgium']
def plot_worldmap(results, cmap=['#ff0000'], showfig=True, verbose=3):
"""Plot results on the worldmap derived from googletrends.spatio().
Parameters
----------
results : dict
results are derived from the temporal() function.
figsize : tuple, optional
Figure size (height, width). The default is 'auto'.
showfig : bool, optional
When True, auto open the map figures in your browser. The default is 'True'.
verbose : int, optional
Print message to screen. The default is 3.
Returns
-------
dict containing results.
Examples
--------
>>> # Trending results
>>> result = googletrends.spatio(['corona','covid-19'], geo=['nl','italy'], date_start='01-12-2019')
>>> googletrends.plot_worldmap(results_spatio)
"""
out = None
if verbose >= 3:
print('[googletrends] Superimposing geographical results on worldmap.')
df = []
county_names = []
for geo_name in results['geo']:
dftmp = results[geo_name]['df']
dftmp['geo'] = worldmap.code2county(geo_name)[1]
df.append(dftmp)
# Combine data in 1 dataframe
df = pd.concat(df, axis=0)
df = df.groupby(by='geo').sum()
data, colnames, idx_names = _normalize_data(df)
for i in range(0, data.shape[1]):
# Color only those with value>0
idx = np.where(data[:, i] > 0)[0]
county_names = idx_names[idx]
opacity = data[idx, i]
filename = colnames[i] + '_worldmap.svg'
# If no data, set all on black
if len(county_names) == 0:
county_names = idx_names
opacity = 1
cmap = ['#D3D3D3']
# Plot on map
out = worldmap.plot(county_names,
map_name='world',
opacity=opacity,
cmap=cmap,
filename=filename,
showfig=showfig)
return (out)
def spatio(searchwords,
geo='',
date_start=None,
date_stop=None,
method='news',
include_suggestions=False,
verbose=3):
"""Gather data for google searches over geographical locations and time.
Parameters
----------
searchwords : list
Lookup each input word and return the (normalized) frequency of google searches.
Example: ['Corona','earth quake']
geo : list, optional
Filter on geographical locations.
'NL' (only netherlands)
['NL','germany','IT']
date_start : str [dd-mm-yyyy]
String: Start date for counting.
date_stop : str [dd-mm-yyyy], optional
String: Stop date for counting. If nothing is filled in, date of today is used.
method : str, optional
Type of google search. The default is 'news'.
Choose on of those: 'images','news','youtube','froogle'
include_suggestions : bool, optional
Include suggestions. The default is False.
verbose : int, optional
Print message to screen. The default is 3.
Raises
------
Exception
code 429: Too Many google requests in a given amount of time ("rate limiting").
Returns
-------
dict containing results.
Examples
--------
>>> result = googletrends.spatio(['corona','covid-19'], geo=['nl','italy'], date_start='01-12-2019')
>>> googletrends.plot(result)
"""
if not check_connection.internet():
raise Exception('No internet connection')
if isinstance(searchwords, str):
searchwords = [searchwords]
if geo == '':
raise Exception('geo should be a string')
if geo == 'world':
geo = get_geo_names()['code'].values
if isinstance(geo, str):
geo = [geo]
# Get data range and message
_, _, date_range = _set_dates(date_start, date_stop, verbose=verbose)
# Convert to country name to code
for i in range(0, len(geo)):
geo[i] = geo[i].upper()
if len(geo[i]) > 3: geo[i] = worldmap.county2code(geo[i])[0][0].upper()
# Search for searchwords
out = {}
for geo_name in geo:
out[geo_name] = _spatio_per_searchword(
searchwords,
geo=geo_name,
date_start=date_start,
date_stop=date_stop,
method=method,
include_suggestions=include_suggestions,
verbose=verbose)
# Fin
out['method'] = 'geo'
out['date_range'] = date_range
out['searchwords'] = searchwords
out['geo'] = geo
out['geo_names'] = list(map(lambda x: worldmap.code2county(x)[1], geo))
# return
return (out)
def trending(searchwords,
geo=None,
date_start=None,
date_stop=None,
method='news',
verbose=3):
""" Gather data for trending google searches.
Description
-----------
If you choose a time period that is 3 months or shorter you get daily data, otherwise you get weekly data.
If the time period is 3 years or longer, the monthly data is plotted, otherwise it is weekly data.
Parameters
----------
searchwords : list
Lookup each input word and return the (normalized) frequency of google searches.
Example: ['Corona','earth quake']
geo : list, optional
Filter on geographical locations.
'NL' (only netherlands),
['NL','germany','IT'],
'world' to examine all countries
date_start : str [dd-mm-yyyy]
String: Start date for counting.
date_stop : str [dd-mm-yyyy], optional
String: Stop date for counting. If nothing is filled in, date of today is used.
method : str, optional
Type of google search. The default is 'news'.
Choose on of those: 'images','news','youtube','froogle'
verbose : int, optional
Print message to screen. The default is 3.
Raises
------
Exception
code 429: Too Many google requests in a given amount of time ("rate limiting").
Returns
-------
dict containing results.
Examples
--------
>>> result = googletrends.spatio(['corona','covid-19'], geo=['nl','italy'], date_start='01-12-2019')
>>> googletrends.plot(result)
>>> # Plot only on the worldmap
>>> googletrends.plot_worldmap(result)
"""
if not check_connection.internet():
raise Exception('No internet connection')
if isinstance(searchwords, str):
searchwords = [searchwords]
if isinstance(geo, str):
geo = [geo]
if geo is None:
raise Exception('parameter [geo] must be provided.')
if geo == 'world':
geo = get_geo_names()['code'].values
# Convert to country name to code
for i in range(0, len(geo)):
geo[i] = geo[i].upper()
if len(geo[i]) > 3:
geo[i] = worldmap.county2code(geo[i])[0][0].upper()
# Get data range and message
_, _, date_range = _set_dates(date_start, date_stop, verbose=verbose)
# Collect data per searchword
df, df_rising, df_top = {}, {}, {}
if verbose >= 3: print('[googletrends]')
for geo_name in geo:
df[geo_name], df_rising[geo_name], df_top[geo_name] = {}, {}, {}
dftmp, dftmp1, dftmp2 = [], [], []
if verbose >= 3: print('--------[%s]--------' % geo_name)
for searchword in searchwords:
try:
# Initialize
pytrends, _ = _initialize([searchword],
date_start,
date_stop,
geo_name,
method,
verbose=0)
# Trending
trending_searches = pytrends.trending_searches(
pn=worldmap.code2county(geo_name)[1].lower())
trending_searches['searchword'] = searchword
dftmp.append(trending_searches)
# Top
related_queries = pytrends.related_queries()
tmptop = pd.DataFrame(related_queries[searchword]['top'])
if not tmptop.empty:
tmptop['searchword'] = searchword
dftmp1.append(tmptop)
# Rising
tmprising = pd.DataFrame(related_queries[searchword]['rising'])
if not tmprising.empty:
tmprising['searchword'] = searchword
dftmp2.append(tmprising)
if verbose >= 3:
print(
'[%s]\n Top: %.0f\n Rising: %.0f\n Trending: %.0f'
% (searchword, tmptop.shape[0], tmprising.shape[0],
trending_searches.shape[0]))
except:
print(
'[googletrends] [%s][%s]: Warning: Could not retrieve informatie. Maybe wrong geo or searchword?'
% (geo_name, searchword))
# Combine data in 1 dataframe
if len(dftmp1) > 0:
dftmp1 = pd.concat(dftmp1, axis=0)
dftmp1.sort_values(by='value',
ascending=False).reset_index(drop=True,
inplace=True)
df_top[geo_name] = dftmp1
if len(dftmp2) > 0:
dftmp2 = pd.concat(dftmp2, axis=0)
dftmp2.sort_values(by='value',
ascending=False).reset_index(drop=True,
inplace=True)
df_rising[geo_name] = dftmp2
if len(dftmp) > 0:
dftmp = pd.concat(dftmp, axis=0)
dftmp.reset_index(drop=True, inplace=True)
df[geo_name] = dftmp
out = {}
out['method'] = 'trending'
out['trending'] = df
out['rising'] = df_rising
out['top'] = df_top
out['geo'] = geo
out['geo_names'] = list(map(lambda x: worldmap.code2county(x)[1], geo))
out['searchwords'] = searchwords
out['date_range'] = date_range
return (out)
def temporal(searchwords,
geo=None,
date_start=None,
date_stop=None,
method='news',
verbose=3):
""" Gather data for google searches over time.
Parameters
----------
searchwords : list
Lookup each input word and return the (normalized) frequency of google searches.
Example: ['Corona','earth quake']
geo : list, optional
Filter on geographical locations.
'NL' (only netherlands)
['NL','germany','IT']
date_start : str [dd-mm-yyyy]
String: Start date for counting.
date_stop : str [dd-mm-yyyy], optional
String: Stop date for counting. If nothing is filled in, date of today is used.
method : str, optional
Type of google search. The default is 'news'.
Choose on of those: 'images','news','youtube','froogle'
verbose : int, optional
Print message to screen. The default is 3.
Raises
------
Exception
code 429: Too Many google requests in a given amount of time ("rate limiting").
Returns
-------
dict containing results.
Examples
--------
>>> result = googletrends.temporal(['corona','covid-19'], geo=['nl','italy'], date_start='01-12-2019')
>>> googletrends.plot(result)
"""
if not check_connection.internet():
raise Exception('No internet connection')
if isinstance(searchwords, str):
searchwords = [searchwords]
if geo == 'world':
geo = get_geo_names()['code'].values
if isinstance(geo, str):
geo = [geo]
if verbose >= 3:
print(
'[googletrends] Collecting trends over time for geographically: %s'
% (geo))
# Get data range and message
_, _, date_range = _set_dates(date_start, date_stop, verbose=verbose)
# Convert to country name to code
for i in range(0, len(geo)):
geo[i] = geo[i].upper()
if len(geo[i]) > 3:
geo[i] = worldmap.county2code(geo[i])[0][0].upper()
# Collect data per searchword
df_geo = {}
for geo_name in geo:
dftmp = []
for searchword in searchwords:
try:
if verbose >= 3:
print('[googletrends] [%s] Working on %s..' %
(geo_name, searchword))
pytrends, geo_name = _initialize([searchword],
date_start,
date_stop,
geo_name,
method,
verbose=0)
data_time = pytrends.interest_over_time()
if not data_time.empty:
data_time.sort_values('date', inplace=True)
dftmp.append(data_time[[searchword]])
except:
if verbose >= 2:
print('[googletrends] [%s] Failed %s..' %
(geo_name, searchword))
# Combine data in 1 dataframe
if len(dftmp) > 0:
dftmp = pd.concat(dftmp, axis=1)
dftmp.reset_index(inplace=True, drop=False)
df_geo[geo_name] = {}
df_geo[geo_name] = dftmp
else:
df_geo = pd.DataFrame()
out = {}
out['method'] = 'temporal'
out['df'] = df_geo
out['geo'] = geo
out['geo_names'] = list(map(lambda x: worldmap.code2county(x)[1], geo))
out['searchwords'] = searchwords
out['date_range'] = date_range
return (out)