Summary Statistics History

This notebook showcases the use of the inventor_summary_trend_plot() function to easily plot the history of key summary statistics (matching rate, homonymy rate, and name variation rate) for PatentsView.org.

Step 1: Download Required Files

The first step is to download required files, namely “g_persistent_inventor.tsv” and “g_inventor_not_disambiguated.tsv” from PatentsView’s bulk data downloads. The first file contains the disambiguation history. The second file is used to obtain inventor names.

import pandas as pd
import wget
import zipfile
import os
from urllib.parse import urlparse

import plotly.graph_objects as go
import plotly.io as pio
pio.templates.default = "plotly_white" # Set plotly theme

def download_unzip(url, overwrite=False):
    basename = os.path.basename(urlparse(url).path)
    filename = basename.rstrip(".zip")
    if not os.path.isfile(filename) or overwrite:
        wget.download(url)
        with zipfile.ZipFile(basename, 'r') as zip_ref:
            zip_ref.extractall(".")
        os.remove(basename)
    return filename

persistent_inventor_file = download_unzip("https://s3.amazonaws.com/data.patentsview.org/download/g_persistent_inventor.tsv.zip")
inventor_not_disambiguated_file = download_unzip("https://s3.amazonaws.com/data.patentsview.org/download/g_inventor_not_disambiguated.tsv.zip")

persistent_inventor = pd.read_csv(persistent_inventor_file, sep="\t", dtype=str)
inventor_not_disambiguated = pd.read_csv(inventor_not_disambiguated_file, sep="\t", dtype=str)

Step 2: Compute Inventor Mention Names

We now recover names associated with each inventor mention.

inventor_not_disambiguated["mention_id"] = "US" + inventor_not_disambiguated.patent_id + "-" + inventor_not_disambiguated.inventor_sequence
inventor_not_disambiguated["name"] = inventor_not_disambiguated.raw_inventor_name_first + " " + inventor_not_disambiguated.raw_inventor_name_last
inventor_not_disambiguated.set_index("mention_id", inplace=True)
names = inventor_not_disambiguated["name"]

Step 3: Plot Summary Statistics History

The persistent_inventor and names DataFrame can now be passed to inventor_summary_trend_plot() to obtain the summary statistics history.

from pv_evaluation.benchmark import inventor_summary_trend_plot

fig = inventor_summary_trend_plot(persistent_inventor, names)
fig.show(renderer="svg")

The plot is tweaked below.

fig.update_layout(
    width=800,
    height=300,
    title="Summary Statistics"
)
fig['layout'].update(margin=dict(l=20,r=20,b=20,t=60))

fig.write_image("summary_trend.pdf")
fig.show(renderer="svg")