Analyzing Text Content of all Ontologies

!mkdir -p output

!python -m oaklib.utilities.metrics.text_content_analysis ~/repos/semantic-sql/db/*.db > output/ontologies-tc.tsv

import pandas as pd
df = pd.read_csv('output/ontologies-tc.tsv', sep='\t')
df

	ontology	text_content
0	/Users/cjm/repos/semantic-sql/db/aao.db	NaN
1	/Users/cjm/repos/semantic-sql/db/ado.db	0.945262
2	/Users/cjm/repos/semantic-sql/db/adw.db	NaN
3	/Users/cjm/repos/semantic-sql/db/aeo.db	0.879694
4	/Users/cjm/repos/semantic-sql/db/aero.db	NaN
...	...	...
145	/Users/cjm/repos/semantic-sql/db/go-lego.db	0.589013
146	/Users/cjm/repos/semantic-sql/db/go-nucleus.db	0.846068
147	/Users/cjm/repos/semantic-sql/db/go-plus.db	0.500000
148	/Users/cjm/repos/semantic-sql/db/go.db	0.604229
149	/Users/cjm/repos/semantic-sql/db/goa_uniprot_a...	NaN

150 rows × 2 columns

# replace ontology column (which is currently file path) with ontology name (stemmed file name)
import os
df['ontology'] = df['ontology'].apply(lambda x: os.path.basename(x).replace('.db',''))
df

	ontology	text_content
0	aao	NaN
1	ado	0.945262
2	adw	NaN
3	aeo	0.879694
4	aero	NaN
...	...	...
145	go-lego	0.589013
146	go-nucleus	0.846068
147	go-plus	0.500000
148	go	0.604229
149	goa_uniprot_all	NaN

150 rows × 2 columns

# drop columns with all text_content values as NaN
df = df.dropna()
df

	ontology	text_content
1	ado	0.945262
3	aeo	0.879694
5	agro	0.801219
6	aio	0.940620
7	aism	0.684825
...	...	...
144	go-amigo	0.592075
145	go-lego	0.589013
146	go-nucleus	0.846068
147	go-plus	0.500000
148	go	0.604229

126 rows × 2 columns

Plot Results

use matplotlib to plot the results as a bar chart, ordered by the text_content value

# use matplotlib to plot df as a bar chart
# x-axis: ontology
# y-axis: text_content
# order by text_content

import matplotlib.pyplot as plt
import seaborn as sns

df = df.sort_values('text_content', ascending=False)
plt.figure(figsize=(24, 12))
sns.barplot(x='ontology', y='text_content', data=df)
plt.xticks(rotation=90)
plt.xlabel('Ontology')
plt.ylabel('Text Content')
plt.title('Text Content of Ontologies')
plt.savefig('output/text_content.png')
plt.savefig('output/text_content.svg')
plt.show()