Google Trends¶
Google Trends has data going back to January 1, 2004 about the frequencies of search terms, which can be imported into a pandas DataFrame using the pytrends library.
We can use various methods such as interest_over_time() or interest_by_region.
#install the pytrends package
!pip install --user pytrends
Requirement already satisfied: pytrends in /home/mikel/.local/lib/python3.7/site-packages (4.7.3)
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from pytrends.request import TrendReq
import pandas as pd
pytrend = TrendReq()
pytrend.build_payload(kw_list=['Mars', 'Venus'])
df = pytrend.interest_over_time()
df
| Mars | Venus | isPartial | |
|---|---|---|---|
| date | |||
| 2015-09-27 | 100 | 17 | False |
| 2015-10-04 | 42 | 15 | False |
| 2015-10-11 | 39 | 17 | False |
| 2015-10-18 | 37 | 15 | False |
| 2015-10-25 | 36 | 15 | False |
| ... | ... | ... | ... |
| 2020-08-16 | 21 | 15 | False |
| 2020-08-23 | 23 | 14 | False |
| 2020-08-30 | 22 | 16 | False |
| 2020-09-06 | 27 | 15 | False |
| 2020-09-13 | 26 | 36 | True |
260 rows × 3 columns
