Sklearn Iris Dataset - Load The Iris Dataset & Split Into Features & Target

Python

 1|  from sklearn.datasets import load_iris
 2|  
 3|  iris = load_iris()
 4|  
 5|  X = pd.DataFrame(data=iris['data'],
 6|                   columns= iris['feature_names'])
 7|  y = pd.Series(diabetes['target'])
detro
Sklearn | Iris
Did you find this snippet useful?

Sign up for free to to add this to your code library

Remove Stop Words from Text in DataFrame Column
Python

Pandas | Nltk | Nlp

143
LightGBM Custom Loss Function
Python

LightGBM | Loss function

128
Tuning XGBoost Hyperparameters with Grid Search
Python

XGBoost | Tuning

123
How to Convert DataFrame Values Into Percentages
Python

Lambda | Percentages | Pipe

116
How to Scale Data Using Standard Scaler But Keep Column Names
Python

Scaler | Standard

87
LightGBM Hyperparameter Tuning with GridSearch
Python

Python | LightGBM | Hyperparameter tuning | Gridsearch

86
Calculating Root Mean Squared Error (RMSE) with Sklearn and Python
Python

Rmse

82
Dynamically Create Columns in Pandas Dataframe
Python

Pandas | Columns

66
How to Train a Catboost Classifier with GridSearch Hyperparameter Tuning
Python

Catboost | Hyperparameter tuning

65
Overwriting a Python Logging File Instead of Appending
Python

Logging

62