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import numpy as np
import pandas as pd

df = pd.DataFrame(data=[[1, 2, 3], [4, 5, 6]], columns=['a', 'b', 'c'])
print(df)

a_df = df.values
print(a_df)

print(type(a_df))

print(a_df.dtype)

s = df['a']
print(s)

a_s = s.values
print(a_s)

print(type(a_s))

print(a_s.dtype)

df_f = pd.DataFrame([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]])
print(df_f)

a_df_f = df_f.values
print(a_df_f)

print(type(a_df_f))

print(a_df_f.dtype)

df_multi = pd.read_csv('data/src/sample_pandas_normal.csv')
print(df_multi)

a_df_multi = df_multi.values
print(a_df_multi)

print(type(a_df_multi))

print(a_df_multi.dtype)

a_df_int = df_multi[['age', 'point']].values
print(a_df_int)

print(type(a_df_int))

print(a_df_int.dtype)

print(a_df_int.T)

a_df_int = df_multi.select_dtypes(include=int).values
print(a_df_int)

print(type(a_df_int))

print(a_df_int.dtype)

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