def post(self, request, **kwargs):
if 'submit' in request.POST:
name=request.POST['name']
gp = GenderPredictor()
gp.train_and_test()
detected_gender = gp.classify(name)
context = {
"name" : name,
"gender": detected_gender
}
return render(request, 'gender_app/predict_gender.html',context)
col3.append(10)
col3.append(10)
col3.append(12)
col3.append(10)
col3.append(11)
col3.append(12)
col3.append(10)
col3.append(10)
col3.append(9)
col3.append(9)
col3.append(9)
print(len(col3))
data_dict['Grade'] = col3
print(len(data_dict['Grade']))
# Getting the gender
gen = GenderPredictor()
gen.train_and_test()
col4 = [gen.classify(i.split(" ")[0]) for i in col1]
print(col4)
data_dict['Gender'] = col4
df = pd.DataFrame.from_dict(data_dict)
df.head()
df.replace('M', 'male', inplace=True)
df.replace('F', 'female', inplace=True)
df.to_csv("data/m132-student-data.csv")
import pandas as pd
from os import getcwd, listdir
from gender_predictor import GenderPredictor
# Get the Student Data
data_path = getcwd() + "/data"
listdir(data_path)
df = pd.read_csv(f"{data_path}/{listdir(data_path)[0]}")
# Instantiate the Class
gp = GenderPredictor()
# Train the Model
gp.train_and_test()
# Get List of Students' First Names
student_names = [name.split(" ")[0] for name in df['Student Name'].tolist()]
# Get Predictions
gender_preds = [gp.classify(name) for name in student_names]
# Add Gender Column to the Data Frame
df['Gender'] = gender_preds
# Save New Data
df.to_csv(f"{data_path}/{listdir(data_path)[0]}", index=False)
df['Gender']