import pandas as pd

# Define the file path and its name
path_to_file = 'path/to/file'
file_name = 'DYToMuMu_M-20_CT10_TuneZ2star_v2_8TeV_0.feather'

# Read the feather file
df = pd.read_feather(f'{path_to_file}/{file_name}')

# This will result in an overview of the actual DataFrame, see below for an example
print(df)
"""
       nEvent  runNum  lumisection  ...  HLT_MET120_v  HLT_Ele27 HLT_HT350
0           1  206859      62190.0  ...         False      False     False
1           2  206859      62190.0  ...         False      False     False
2           3  206859      62190.0  ...         False      False     False
3           4  206859      62190.0  ...         False      False     False
4           5  206859      62190.0  ...         False      False     False
...       ...     ...          ...  ...           ...        ...       ...
13176   13177  206859     164541.0  ...         False      False     False
13177   13178  206859     164541.0  ...         False      False     False
13178   13179  206859     164541.0  ...         False      False     False
13179   13180  206859     164541.0  ...         False      False     False
13180   13181  206859     164541.0  ...         False      False     False

[13181 rows x 121 columns]
"""

# Select a single variable, this will basically return a DataFrame with a single column
vecMuon_PT = df['vecMuon_PT']
print(vecMuon_PT)
"""
0                                              [5.8036003]
1                                   [41.354645, 72.184425]
2                                   [13.256983, 12.928027]
3                                   [45.348038, 42.803078]
4                                     [42.90248, 47.64194]
                               ...                        
13176    [33.999542, 1.080644, 28.602516, 1.5932022, 0....
13177    [21.556686, 15.966783, 1.6068497, 1.1789985, 0...
13178                    [1.2909112, 1.0356978, 0.9334271]
13179                                 [9.293548, 7.838468]
13180                                            [17.1877]
Name: vecMuon_PT, Length: 13181, dtype: object
"""


# It is also possible to parse the column to a numpy array
vecMuon_PT = df['vecMuon_PT'].to_numpy()
print(vecMuon_PT)
"""
[array([5.8036003], dtype=float32)
 array([41.354645, 72.184425], dtype=float32)
 array([13.256983, 12.928027], dtype=float32) ...
 array([1.2909112, 1.0356978, 0.9334271], dtype=float32)
 array([9.293548, 7.838468], dtype=float32)
 array([17.1877], dtype=float32)]
 """