Scikit Learn metrics to Pandas DataFrame

scikitlearn2pandas.py

from sklearn.metrics import classification_report, confusion_matrix
import pandas as pd

def get_df_classification_report(y_test, y_pred, target_names):
    '''Source: https://stackoverflow.com/questions/39662398/scikit-learn-output-metrics-classification-report-into-csv-tab-delimited-format'''
    report = classification_report(y_test, y_pred, output_dict=True, target_names=target_names)
    df = pd.DataFrame(report).transpose()
    return df.round(decimals=3)

# example
'''
y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
target_names = ['類別1', '類別2', '類別3']
df = get_df_classification_report(y_true, y_pred, target_names)
'''

#source: https://gist.github.com/nickynicolson/202fe765c99af49acb20ea9f77b6255e
def get_df_confusion_matrix(y_true, y_pred, labels):
    cm = confusion_matrix(y_true, y_pred)
    df = pd.DataFrame()
    # rows
    for i, row_label in enumerate(labels):
        rowdata={}
        # columns
        for j, col_label in enumerate(labels): 
            rowdata[col_label]=cm[i,j]
        df = df.append(pd.DataFrame.from_dict({row_label:rowdata}, orient='index'))
    return df[labels]

# example
'''
y_true = ["cat", "ant", "cat", "cat", "ant", "bird"]
y_pred = ["ant", "ant", "cat", "cat", "ant", "cat"]
labels= ["ant", "bird", "cat"]
df = get_df_confusion_matrix(y_true, y_pred, labels)
'''