f70e71d5c7fdc8e25391e54e74c3402fb323ad5c,examples/plot_employee_salaries.py,,,#,45
Before Change
// the rest will have a standard encoding
data_path = fetching.get_data_dir()
fetching.fetch_employee_salaries()
data_file = os.path.join(data_path, "employee_salaries", "rows.csv")
df = pd.read_csv(data_file).astype(str)
df["Current Annual Salary"] = [float(s[1:]) for s
in df["Current Annual Salary"]]
df["Year First Hired"] = [int(s.split("/")[-1])
for s in df["Date First Hired"]]
target_column = "Current Annual Salary"
y = df[target_column].values.ravel()
After Change
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// and carry out some basic preprocessing:
df["Current Annual Salary"] = df["Current Annual Salary"].str.strip("$").astype(
float)
df["Date First Hired"] = pd.to_datetime(df["Date First Hired"])
df["Year First Hired"] = df["Date First Hired"].apply(lambda x: x.year)
target_column = "Current Annual Salary"
y = df[target_column].values.ravel()
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 7
Instances
Project Name: dirty-cat/dirty_cat
Commit Name: f70e71d5c7fdc8e25391e54e74c3402fb323ad5c
Time: 2018-06-06
Author: pierreglaser@msn.com
File Name: examples/plot_employee_salaries.py
Class Name:
Method Name:
Project Name: gboeing/osmnx
Commit Name: 3fefc7642179e021dfd2c9ec43ece3a98c3663df
Time: 2020-12-22
Author: boeing@usc.edu
File Name: osmnx/geocoder.py
Class Name:
Method Name: _geocode_query_to_gdf
Project Name: PyMVPA/PyMVPA
Commit Name: 5bc47f908692c2c46173eb2451960816b6d0b58e
Time: 2010-01-10
Author: psederberg@gmail.com
File Name: mvpa/clfs/glmnet.py
Class Name: _GLMNET
Method Name: _predict