image_output_11.png image_output_14.png image_output_13.png image_output_5.png image_output_7.png image_output_4.png image_output_8.png image_output_6.png image_output_12.png image_output_3.png image_output_2.png image_output_1.png image_output_10.png image_output_9.png
import pandas as pd

lb_data = pd.read_csv('../input/leaderboard-4-days-out/jigsaw-unintended-bias-in-toxicity-classification-publicleaderboard.csv')

lb_data = lb_data.set_index('SubmissionDate')

top_15_teams = lb_data.groupby('TeamId').max().sort_values('Score')[-15:]['TeamName'].values

top_15_subs = lb_data.loc[lb_data['TeamName'].isin(top_15_teams)]

top_15_subs = top_15_subs.drop('TeamId', axis=1)

top_15_subs.pivot(columns='TeamName', values='Score')

for i in top_15_subs.pivot(columns='TeamName', values='Score').interpolate():
    print(top_15_subs.pivot(columns='TeamName', values='Score')[i].dropna())