Making a pandas dataframe from a .npy file
Let's assume once you load the .npy
, the item (np.load(path_to_use).item()
) looks similar to this;
{'user_c': 'id_003', 'user_a': 'id_001', 'user_b': 'id_002'}
So, if you need to come up with a DataFrame like below using above dictionary;
user_name user_id
0 user_c id_003
1 user_a id_001
2 user_b id_002
You can use;
df = pd.DataFrame(list(x.item().iteritems()), columns=['user_name','user_id'])
If you have a list of dictionaries like below;
users = [{'u_name': 'user_a', 'u_id': 'id_001'}, {'u_name': 'user_b', 'u_id': 'id_002'}]
You can simply use
df = pd.DataFrame(users)
To come up with a DataFrame similar to;
u_id u_name
0 id_001 user_a
1 id_002 user_b
Seems like you have a dictionary similar to this;
data = {
'Center': [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]],
'Vpeak': [1.1, 2.2],
'ID': ['id_001', 'id_002']
}
In this case, you can simply use;
df = pd.DataFrame(data) # df = pd.DataFrame(file_dict.item()) in your case
To come up with a DataFrame similar to;
Center ID Vpeak
0 [0.1, 0.2, 0.3] id_001 1.1
1 [0.4, 0.5, 0.6] id_002 2.2
If you have ndarray
within the dict, do some preprocessing similar to below; and use it to create the df;
for key in data:
if isinstance(data[key], np.ndarray):
data[key] = data[key].tolist()
df = pd.DataFrame(data)
Arnold
Updated on June 04, 2022Comments
-
Arnold almost 2 years
I'm trying to make a pandas dataframe from a .npy file which, when read in using np.load, returns a numpy array containing a dictionary. My initial instinct was to extract the dictionary and then create a dataframe using pd.from_dict, but this fails every time because I can't seem to get the dictionary out of the array returned from np.load. It looks like it's just np.array([dictionary, dtype=object]), but I can't get the dictionary by indexing the array or anything like that. I've also tried using np.load('filename').item() but the result still isn't recognized by pandas as a dictionary.
Alternatively, I tried pd.read_pickle and that didn't work either.
How can I get this .npy dictionary into my dataframe? Here's the code that keeps failing...
import pandas as pd import numpy as np import os targetdir = '../test_dir/' filenames = [] successful = [] unsuccessful = [] for dirs, subdirs, files in os.walk(targetdir): for name in files: filenames.append(name) path_to_use = os.path.join(dirs, name) if path_to_use.endswith('.npy'): try: file_dict = np.load(path_to_use).item() df = pd.from_dict(file_dict) #df = pd.read_pickle(path_to_use) successful.append(path_to_use) except: unsuccessful.append(path_to_use) continue print str(len(successful)) + " files were loaded successfully!" print "The following files were not loaded:" for item in unsuccessful: print item + "\n" print df