00.write_csv

In [1]:

import pandas as pd
import numpy as np

In [2]:

# 털, 날개, 기타, 포유류, 조류
col_list = ["hair", "wing", "etc", "mammals", "bird"]
classification_ex = pd.DataFrame({
    "hair": [0, 1, 1, 0, 0, 0],
    "wing": [0, 0, 1, 0 ,0 ,1],
    "bird": [1, 0, 0, 1, 1, 0],
    "etc" : [0, 1, 0, 0, 0, 0],
    "mammals": [0, 0, 1 ,0 ,0 ,1]   
}, columns=col_list)

classification_ex.to_csv("./datas/classification_ex1.csv", 
                         encoding="utf-8",
                        index=False) # header=False

In [3]:

## iris_data
from sklearn.datasets import load_iris

iris = load_iris()
iris_values = np.hstack([iris.data, iris.target.reshape(-1, 1)])

col_names = ["sepal_length", "sepal_width", "petal_length", "petal_width", "species"]
iris_data = pd.DataFrame(data=iris_values, columns=col_names)

iris_data["species"].replace(to_replace=0.0, value="setosa", inplace=True)
iris_data["species"].replace(to_replace=1.0, value="versicolor", inplace=True)
iris_data["species"].replace(to_replace=2.0, value="virginica", inplace=True)

iris_data.to_csv("./datas/iris.csv", encoding="utf-8", index=False)

In [4]:

## breast_cancer
from sklearn.datasets import load_breast_cancer

cancer = load_breast_cancer()
cancer_values = np.hstack([cancer.data, cancer.target.reshape(-1, 1)])

col_names = np.hstack([cancer.feature_names, "result"])
cancer_data = pd.DataFrame(data=cancer_values, columns=col_names)

cancer_data["result"].replace(to_replace=0, value="malignant", inplace=True)
cancer_data["result"].replace(to_replace=1, value="benign", inplace=True)

cancer_data.to_csv("./datas/cancer.csv", encoding="utf-8", index=False)

In [5]:

from IPython.core.display import display, HTML
display(HTML("<style> .container{width:100% !important;}</style>"))