import pandas as pd
data_dict = {'one': pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two': pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(data_dict)
print(f"DataFrame:
{df}
")
print(f"column types:
{df.dtypes}")
col_one_list = df['one'].tolist()
col_one_arr = df['one'].to_numpy()
print(f"
col_one_list:
{col_one_list}
type:{type(col_one_list)}")
print(f"
col_one_arr:
{col_one_arr}
type:{type(col_one_arr)}")
In [8]: data = pd.DataFrame({'x': x, 'sin(x)': y})
In [9]: data
Out[9]:
x sin(x)
0 0.000000 0.000000e+00
1 0.349066 3.420201e-01
2 0.698132 6.427876e-01
3 1.047198 8.660254e-01
4 1.396263 9.848078e-01
5 1.745329 9.848078e-01
6 2.094395 8.660254e-01
7 2.443461 6.427876e-01
8 2.792527 3.420201e-01
9 3.141593 1.224647e-16
[10 rows x 2 columns]
df_gearME = pd.read_excel('Gear M&Es.xlsx')
df_gearME['ColA'].to_list()
import pandas as pd
lst = [1,2,3]
df = pd.DataFrame([lst])
df.columns =['col1','col2','col3']
df
to get this:
col1 col2 col3
0 1 2 3
from ast import literal_eval
df.Col3 = df.Col3.apply(literal_eval)
print(df.Col3[0][0])
Proj1