Movatterモバイル変換

[0]ホーム
URL:

Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

 Sign up
Appearance settings

Commit3b3c341

Browse files
committed
add extracing google trends data tutorial
1 parentc2bf474 commit3b3c341

File tree

5 files changed

+329
-0
lines changed

5 files changed

+329
-0
lines changed

‎README.md

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -116,6 +116,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
116116
-[Automated Browser Testing with Edge and Selenium in Python](https://www.thepythoncode.com/article/automated-browser-testing-with-edge-and-selenium-in-python). ([code](web-scraping/selenium-edge-browser))
117117
-[How to Automate Login using Selenium in Python](https://www.thepythoncode.com/article/automate-login-to-websites-using-selenium-in-python). ([code](web-scraping/automate-login))
118118
-[How to Make a Currency Converter in Python](https://www.thepythoncode.com/article/make-a-currency-converter-in-python). ([code](web-scraping/currency-converter))
119+
-[[How to Extract Google Trends Data in Python](https://www.thepythoncode.com/article/extract-google-trends-data-in-python). ([code](web-scraping/extract-google-trends-data))]
119120

120121
-###[Python Standard Library](https://www.thepythoncode.com/topic/python-standard-library)
121122
-[How to Transfer Files in the Network using Sockets in Python](https://www.thepythoncode.com/article/send-receive-files-using-sockets-python). ([code](general/transfer-files/))
Lines changed: 256 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,256 @@
1+
{
2+
"cells": [
3+
{
4+
"cell_type":"code",
5+
"execution_count":null,
6+
"metadata": {
7+
"colab": {
8+
"base_uri":"https://localhost:8080/"
9+
},
10+
"id":"Mzt6JmpwLnl0",
11+
"outputId":"bb600d41-0b2f-4c7e-ab47-0e645277988b"
12+
},
13+
"outputs": [],
14+
"source": [
15+
"!pip install pytrends"
16+
]
17+
},
18+
{
19+
"cell_type":"code",
20+
"execution_count":null,
21+
"metadata": {
22+
"id":"9S9Szn46Lp65"
23+
},
24+
"outputs": [],
25+
"source": [
26+
"from pytrends.request import TrendReq\n",
27+
"import seaborn\n",
28+
"# for styling\n",
29+
"seaborn.set_style(\"darkgrid\")\n",
30+
"\n",
31+
"# initialize a new Google Trends Request Object\n",
32+
"pt = TrendReq(hl=\"en-US\", tz=360)"
33+
]
34+
},
35+
{
36+
"cell_type":"code",
37+
"execution_count":null,
38+
"metadata": {
39+
"id":"_3hktMxsLq4M"
40+
},
41+
"outputs": [],
42+
"source": [
43+
"# set the keyword & timeframe\n",
44+
"pt.build_payload([\"Python\",\"Java\"], timeframe=\"all\")"
45+
]
46+
},
47+
{
48+
"cell_type":"code",
49+
"execution_count":null,
50+
"metadata": {
51+
"colab": {
52+
"base_uri":"https://localhost:8080/",
53+
"height":455
54+
},
55+
"id":"5bj7PEPZLruO",
56+
"outputId":"94d313cb-c106-43e8-921f-edc7b7a82ec3"
57+
},
58+
"outputs": [],
59+
"source": [
60+
"# get the interest over time\n",
61+
"iot = pt.interest_over_time()\n",
62+
"iot"
63+
]
64+
},
65+
{
66+
"cell_type":"code",
67+
"execution_count":null,
68+
"metadata": {
69+
"colab": {
70+
"base_uri":"https://localhost:8080/",
71+
"height":406
72+
},
73+
"id":"BG8uQd3zLsw-",
74+
"outputId":"1f9d7327-bad5-4d05-8b1d-046c7527864c"
75+
},
76+
"outputs": [],
77+
"source": [
78+
"# plot it\n",
79+
"iot.plot(figsize=(10, 6))"
80+
]
81+
},
82+
{
83+
"cell_type":"code",
84+
"execution_count":null,
85+
"metadata": {
86+
"colab": {
87+
"base_uri":"https://localhost:8080/",
88+
"height":455
89+
},
90+
"id":"65qkNWguL8g-",
91+
"outputId":"43332253-4215-48f7-e25a-c4dcc2a9f99a"
92+
},
93+
"outputs": [],
94+
"source": [
95+
"# get hourly historical interest\n",
96+
"data = pt.get_historical_interest(\n",
97+
" [\"data science\"],\n",
98+
" cat=396,\n",
99+
" year_start=2022, month_start=1, day_start=1, hour_start=0,\n",
100+
" year_end=2022, month_end=2, day_end=10, hour_end=23,\n",
101+
")\n",
102+
"data"
103+
]
104+
},
105+
{
106+
"cell_type":"code",
107+
"execution_count":null,
108+
"metadata": {
109+
"id":"NYoPNiSiVWFo"
110+
},
111+
"outputs": [],
112+
"source": [
113+
"# the keyword to extract data\n",
114+
"kw =\"python\"\n",
115+
"pt.build_payload([kw], timeframe=\"all\")\n",
116+
"# get the interest by country\n",
117+
"ibr = pt.interest_by_region(\"COUNTRY\", inc_low_vol=True, inc_geo_code=True)"
118+
]
119+
},
120+
{
121+
"cell_type":"code",
122+
"execution_count":null,
123+
"metadata": {
124+
"colab": {
125+
"base_uri":"https://localhost:8080/"
126+
},
127+
"id":"bjWBRVS-XNfo",
128+
"outputId":"db776b26-2487-4ba1-d096-9c84dec93d1f"
129+
},
130+
"outputs": [],
131+
"source": [
132+
"# sort the countries by interest\n",
133+
"ibr[kw].sort_values(ascending=False)"
134+
]
135+
},
136+
{
137+
"cell_type":"code",
138+
"execution_count":null,
139+
"metadata": {
140+
"colab": {
141+
"base_uri":"https://localhost:8080/",
142+
"height":833
143+
},
144+
"id":"ny8R1DKBXON4",
145+
"outputId":"8abbf1af-a186-42ea-91a2-56c5bd165f7d"
146+
},
147+
"outputs": [],
148+
"source": [
149+
"# get related topics of the keyword\n",
150+
"rt = pt.related_topics()\n",
151+
"rt[kw][\"top\"]"
152+
]
153+
},
154+
{
155+
"cell_type":"code",
156+
"execution_count":null,
157+
"metadata": {
158+
"colab": {
159+
"base_uri":"https://localhost:8080/",
160+
"height":833
161+
},
162+
"id":"dCXqM2uBXv7M",
163+
"outputId":"686c8144-50f5-445c-929f-dfda1494a38b"
164+
},
165+
"outputs": [],
166+
"source": [
167+
"# get related queries to previous keyword\n",
168+
"rq = pt.related_queries()\n",
169+
"rq[kw][\"top\"]"
170+
]
171+
},
172+
{
173+
"cell_type":"code",
174+
"execution_count":null,
175+
"metadata": {
176+
"colab": {
177+
"base_uri":"https://localhost:8080/"
178+
},
179+
"id":"FYCQ-ejxZv40",
180+
"outputId":"2ee09da5-6d19-4ba1-c44a-5dd15a683387"
181+
},
182+
"outputs": [],
183+
"source": [
184+
"# get suggested searches\n",
185+
"pt.suggestions(\"python\")"
186+
]
187+
},
188+
{
189+
"cell_type":"code",
190+
"execution_count":null,
191+
"metadata": {
192+
"colab": {
193+
"base_uri":"https://localhost:8080/"
194+
},
195+
"id":"jFvUTnBBaYTS",
196+
"outputId":"95ca6d7d-f801-467d-ade1-e2d5c009bcf5"
197+
},
198+
"outputs": [],
199+
"source": [
200+
"# another example of suggested searches\n",
201+
"pt.suggestions(\"America\")"
202+
]
203+
},
204+
{
205+
"cell_type":"code",
206+
"execution_count":null,
207+
"metadata": {
208+
"colab": {
209+
"base_uri":"https://localhost:8080/",
210+
"height":676
211+
},
212+
"id":"AEKb0IY0YLSx",
213+
"outputId":"8c4519ba-143b-48e2-fc87-b5c5d9a7d56f"
214+
},
215+
"outputs": [],
216+
"source": [
217+
"# trending searches per region\n",
218+
"ts = pt.trending_searches(pn=\"united_kingdom\")\n",
219+
"ts"
220+
]
221+
},
222+
{
223+
"cell_type":"code",
224+
"execution_count":null,
225+
"metadata": {
226+
"colab": {
227+
"base_uri":"https://localhost:8080/",
228+
"height":423
229+
},
230+
"id":"vFDybnL-YaiF",
231+
"outputId":"c826398b-6a1f-4bc2-f5b8-1c1b8ea8f0f8"
232+
},
233+
"outputs": [],
234+
"source": [
235+
"# real-time trending searches\n",
236+
"pt.realtime_trending_searches()"
237+
]
238+
}
239+
],
240+
"metadata": {
241+
"colab": {
242+
"collapsed_sections": [],
243+
"name":"Extracting-GoogleTrends-Data_PythonCodeTutorial.ipynb",
244+
"provenance": []
245+
},
246+
"kernelspec": {
247+
"display_name":"Python 3",
248+
"name":"python3"
249+
},
250+
"language_info": {
251+
"name":"python"
252+
}
253+
},
254+
"nbformat":4,
255+
"nbformat_minor":0
256+
}
Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,3 @@
1+
#[How to Extract Google Trends Data in Python](https://www.thepythoncode.com/article/extract-google-trends-data-in-python)
2+
To run this:
3+
-`pip3 install -r requirements.txt`
Lines changed: 67 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,67 @@
1+
# -*- coding: utf-8 -*-
2+
"""Extracting-GoogleTrends-Data_PythonCodeTutorial.ipynb
3+
4+
Automatically generated by Colaboratory.
5+
6+
Original file is located at
7+
https://colab.research.google.com/drive/1lMX3VemgcfGpiGNlQJNPyivSXHAVYe6O
8+
"""
9+
10+
# !pip install pytrends
11+
12+
frompytrends.requestimportTrendReq
13+
importseaborn
14+
# for styling
15+
seaborn.set_style("darkgrid")
16+
17+
# initialize a new Google Trends Request Object
18+
pt=TrendReq(hl="en-US",tz=360)
19+
20+
# set the keyword & timeframe
21+
pt.build_payload(["Python","Java"],timeframe="all")
22+
23+
# get the interest over time
24+
iot=pt.interest_over_time()
25+
iot
26+
27+
# plot it
28+
iot.plot(figsize=(10,6))
29+
30+
# get hourly historical interest
31+
data=pt.get_historical_interest(
32+
["data science"],
33+
cat=396,
34+
year_start=2022,month_start=1,day_start=1,hour_start=0,
35+
year_end=2022,month_end=2,day_end=10,hour_end=23,
36+
)
37+
data
38+
39+
# the keyword to extract data
40+
kw="python"
41+
pt.build_payload([kw],timeframe="all")
42+
# get the interest by country
43+
ibr=pt.interest_by_region("COUNTRY",inc_low_vol=True,inc_geo_code=True)
44+
45+
# sort the countries by interest
46+
ibr[kw].sort_values(ascending=False)
47+
48+
# get related topics of the keyword
49+
rt=pt.related_topics()
50+
rt[kw]["top"]
51+
52+
# get related queries to previous keyword
53+
rq=pt.related_queries()
54+
rq[kw]["top"]
55+
56+
# get suggested searches
57+
pt.suggestions("python")
58+
59+
# another example of suggested searches
60+
pt.suggestions("America")
61+
62+
# trending searches per region
63+
ts=pt.trending_searches(pn="united_kingdom")
64+
ts
65+
66+
# real-time trending searches
67+
pt.realtime_trending_searches()
Lines changed: 2 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,2 @@
1+
pytrends
2+
seaborn

0 commit comments

Comments
 (0)
[8]ページ先頭
©2009-2025 Movatter.jp