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import numpy as np

import pandas as pd

import warnings

import warnings

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import pandas_profiling as pp
import seaborn as sns
import warnings
import os
import warnings
warnings.filterwarnings(action='ignore')
CSV_PATH = '../input/iris-files/iris.csv'

iris = pd.read_csv(CSV_PATH)

nrow = 5
n_feateures = 4
dates = pd.date_range('20220101', periods=nrow, freq='s')
df = pd.DataFrame(np.random.randn(nrow, n_feateures), index=dates, columns=list('ABCD'))
df

t = np.arange(5)
sin_t = np.sin(t)
cos_t = np.cos(t)
exp_t = np.exp(t)
df2 = pd.DataFrame({'t': t, 'sin': sin_t, 'cos': cos_t, 'exp': exp_t})
df2

df1 = pd.DataFrame(np.random.rand(2, 4))
df2 = pd.DataFrame(np.random.rand(1, 4))
df3 = pd.DataFrame(np.random.rand(3, 5))
df_list = [df1, df2, df3]

df4 = pd.concat(df_list, axis=0)
df4

df5 = pd.concat(df_list, axis=1)
df5

df5.fillna(0)