Decoding WebofScience stats using Python
Using python to find key trends and visualize patterns while conducting literature review
Sanskriti is maintained by Sai Gattupalli, Ph.D., a learning sciences researcher and educator focused on AI-integrated learning environments, culturally responsive computing, and educational equity. Sai earned his doctorate in Learning Technologies from the University of Massachusetts Amherst, where he taught College Writing and collaborated on intelligent tutoring and multimodal learning projects. He writes at the intersection of culture, education, and technology and creates classroom-ready resources—including Equations & Echoes, a YouTube channel of AI-generated STEM music for young learners and teachers.
Written by Sai Gattupalli
In this blog post, you will journey through a dataset supplied by WebofScience that captures a decade of scholarly insights on multicultural education. Using sample Python code, I will distill key trends, visualize patterns, and unravel the nuances of this vital discourse.
import pandas as pd
import matplotlib.pyplot as plt
df_multicultural_tech = pd.read_excel('dataset.xls')
# Extracting relevant data for viz
publications_per_year = df_multicultural_tech['Publication Year'].value_counts().sort_index()
df_multicultural_tech['Country'] = df_multicultural_tech['Addresses'].str.extract(r'([A-Z][A-Z]$)')
publications_per_country = df_multicultural_tech['Country'].value_counts()
all_research_areas = df_multicultural_tech['Research Areas'].str.split(';').explode().str.strip()
publications_per_discipline = all_research_areas.value_counts()
# Plotting the visuals
fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(14, 18))
# Plotting pubs per year
publications_per_year.plot(kind='bar', ax=axes[0], color='skyblue')
axes[0].set_title('Number of Publications Per Year')
axes[0].set_xlabel('Year')
axes[0].set_ylabel('Number of Publications')
# Plotting distribution of pubs by country
publications_per_country.head(10).plot(kind='bar', ax=axes[1], color='lightgreen')
axes[1].set_title('Top 10 Countries with Most Publications')
axes[1].set_xlabel('Country')
axes[1].set_ylabel('Number of Publications')
# Plotting distribution by discipline
publications_per_discipline.head(10).plot(kind='bar', ax=axes[2], color='salmon')
axes[2].set_title('Top 10 Disciplines by Number of Publications')
axes[2].set_xlabel('Discipline')
axes[2].set_ylabel('Number of Publications')
plt.tight_layout()
plt.show()
After supplying data from WoS, here is the output:
Until next time.
