Popular Data Science Questions: Creating a count of nested tags

Screen Link:

My Code:

tag_count = dict()
for tags in posts['Tags']:
    for tag in tags:
        if tag in tag_count:
            tag_count[tag] += 1
        else:
            tag_count[tag] = 1

tag_count

What I expected to happen:
To get a dictionary of all the tags with their counts.

What actually happened:
The tags within each line didn’t get separated. I’ve tried this several different ways (adding all the lists together, using Series.explode() (pandas version isn’t high enough). No matter what I do, I can’t seem to break up the internal list.

{'machine-learning,scikit-learn,data-cleaning,preprocessing': 1,
 'deep-learning,gradient-descent,cs231n,momentum': 1,
 'regression,counts': 1,
 'image-recognition,image-preprocessing,opencv': 1,
 'reinforcement-learning,q-learning,dqn,deep-network': 1,
 'machine-learning,python,linear-regression,gradient-descent': 1,
 'machine-learning,python,predictive-modeling,data-science-model,model-selection': 1,
 'machine-learning,predictive-modeling,xgboost,explainable-ai': 1,
 'machine-learning,time-series,regression,metric': 1,
 'deep-learning,lstm,multiclass-classification,hierarchical-data-format': 1,
 'generative-models,data-imputation': 1,
 'machine-learning,python,predictive-modeling,machine-learning-model': 1,
 'machine-learning,algorithms,unsupervised-learning,data-science-model': 1,
 'python,topic-model,lda,gensim': 1,
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 'time-series,k-means,outlier,dbscan,anomaly': 1,
 'machine-learning,data-mining,visualization,data-analysis': 1,
 'python,tensorflow,dataset,annotation': 1,
 'machine-learning,r,association-rules': 1,
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 'time-series,forecast': 3,
 'loss-function,gan,game': 1,
 'python,neural-network,deep-learning,keras,image-preprocessing': 1,
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 'r,clustering,statistics,k-means': 1,
 'variance': 3,
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 'r,statistics': 4,
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GP- Popular Data Science Questions.ipynb (74.4 KB)

Please share your notebook.

I updated the original post.

1 Like

The default behavior of split is to split on a space, so each list in your series only has 1 item, 1 long string. If you update that line to split on a comma then your code will work.

#split into a list on ','
posts['Tags'] = posts['Tags'].str.split(',')
1 Like

Thanks. That did it. I figured it was something simple.