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Dog Name Creativity

Survey of New York City

We started this project to see if art and cultural institutions in the environment have an impact on the creativity of dognames. This was not possible with the date from Zurich because the name-dataset does not contain information about the location and the dataset about the owners does not include the dognames. We choose to stick with our idea but used a different dataset: NYC Dog Licensing Dataset.

The creativity of a name is measured by the frequency of each letter in the English language and gets +/- points according to the amount of dogs with the same name. The data for the cultural environment comes from Wikidata.

After some data-cleaning with OpenRefine and failed attempts with OpenCalc we got the following code:

import string
import pandas as pd

numbers_ = {"e":1,"t":2,"a":3,"o":4,"n":5,"i":6,"s":7,"h":8,"r":9,"l":10,"d":11,"u":12,"c":13,"m":14,"w":15,"y":16,"f":17,"g":18,"p":19,"b":20,"v":21,"k":22,"j":23,"x":24,"q":25,"z":26}
name_list = []

def KreaWert(name_):
    name_ = str(name_)
    wert_ = 0
    for letter in str.lower(name_):
        temp_ = 0
        if letter in string.ascii_lowercase :
            temp_ += numbers_[letter]
            wert_ += temp_
    if name_ in H_:
        wert_ = wert_* ((Hmax-H_[name_])/(Hmax-1)*5 + 0.2)
    return round(wert_,1)

df = pd.read_csv("Vds3.csv", sep = ";")
df["AnimalName"] = df["AnimalName"].str.strip()
H_ = df["AnimalName"].value_counts()
Hmax = max(H_)
Hmin = min(H_)

df["KreaWert"] = df["AnimalName"].map(KreaWert)
df.to_csv("namen2.csv")

dftemp = df[["AnimalName", "KreaWert"]].drop_duplicates().set_index("AnimalName")
dftemp.to_csv("dftemp.csv")

df3 = pd.DataFrame()
df3["amount"] = H_
df3 = df3.join(dftemp, how="outer")
df3.to_csv("data3.csv")

df1 = round(df.groupby("Borough").mean(),2)
df1.to_csv("data1.csv")

df2 = round(df.groupby(["Borough","AnimalGender"]).mean(),2)
df2.to_csv("data2.csv")

Visualisations were made with D3: https://d3js.org/

Data

Hundedaten der Stadt Zürich:

NYC Dog Licensing Dataset:

Team

  • Birk Weiberg
  • Dominik Sievi