Prostitution in the US: Ethnicity

A look at the ethnicity of US sex workers

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plt.figure(figsize=(10,9))
# limiting the "long tail" at top 30, it's very very long
frame['Ethnicity'].value_counts()[:30].plot(kind="barh");
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Preliminary look at race of providers. Turns out this could use some grouping.

Figuring out ‘ethnicity’ across race and geography

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# Let’s make Ethnicity a little easier to manage and visualize
frame[‘EthnicityNormalized’] = frame.apply(lambda row: normalizedEthnicity(row[‘Ethnicity’],row[‘Country’],row[‘Languages’]), axis=1)
plt.figure(figsize=(10,9))
frame[frame.Country=="USA"]['EthnicityNormalized'].value_counts().plot(kind="pie", label="Ethnicity",autopct='%1.1f%%',
shadow=True, startangle=45);
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Ethnicity (“re-classified” to fall in buckets that made more sense). US breakdown.
plt.figure(figsize=(10,9))
frame[frame.Country.isin(europe)]['EthnicityNormalized'].value_counts().plot(kind="pie", label="Ethnicity",autopct='%1.1f%%',
shadow=True, startangle=45);
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Ethnicity. European breakdown (rough approximation).
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Lots of Latinas in LATAM. Why am I not surprised?

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