image_output_1.png
from warnings import simplefilter

import os

import pandas as pd

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import time

import numpy as np
import pandas as pd
import time
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
pd.set_option('display.width', None)
pd.set_option('display.float_format', lambda x: '%.5f' % x)
from sklearn.utils import shuffle
from warnings import simplefilter
simplefilter(action='ignore', category=FutureWarning)
simplefilter(action='ignore', category=UserWarning)
pd.options.mode.chained_assignment = None
from math import radians, cos, sin, asin, sqrt
import seaborn as sns
import matplotlib.pyplot as plt
from haversine import haversine, Unit
from scipy import stats
from scipy.stats import spearmanr
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from sklearn import preprocessing
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import Pipeline
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import cross_val_score
from sklearn.metrics import mean_squared_log_error
from sklearn.metrics import mean_squared_error
from sklearn.metrics import jaccard_score
from sklearn.metrics import f1_score
from sklearn.ensemble import RandomForestRegressor
import lightgbm as lgbm
import xgboost as xgb
from sklearn.ensemble import VotingRegressor
from sklearn.metrics import roc_auc_score
import os

df = pd.read_csv('/kaggle/input/aapl10y/AAPL10Y.csv')
df['date'] = pd.to_datetime(df['date'])
df.sort_values('date', inplace=True)
df.set_index('date', inplace=True)
print(df.shape)
df.head()