Category : valueerror

Error ScreenShot def read_array(fp, allow_pickle=False, pickle_kwargs=None): version = read_magic(fp) _check_version(version) shape, fortran_order, dtype = _read_array_header(fp, version) if len(shape) == 0: count = 1 else: count = numpy.multiply.reduce(shape, dtype=numpy.int64) # Now read the actual data. if dtype.hasobject: # The array contained Python objects. We need to unpickle the data. **if not allow_pickle: raise ValueError("Object arrays cannot ..

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I can’t get a hold of what is going wrong here. d = {‘x’ : [1,4,6,9], ‘y’ : [1,4,6,8]} df = pd.DataFrame(d) #filter columns based on value in specific row df_VIP = df.iloc[:,df.iloc[1:2,:]<3] I get the error. An this also happens with my real dataframe… ValueError: Buffer has wrong number of dimensions (expected 1, got ..

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I am getting this error while working with a dataset ValueError: cannot set using a multi-index selection indexer with a different length than the value I used this code previously but always run well for the same type of data but now it is not working. for dataset in data_df: dataset.at[dataset[‘Ozone’] <= 54, ‘Ozone’] = ..

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I am training an agent using demonstrations of another agent provided in the form of (state, action, reward, next_state) tuples. I am using Keras and Sklearn. This is how the q learning works: def q_learning_model(): NUM_STATES = len(states) NUM_ACTIONS = 4 GAMMA = 0.99 model_in = tf.keras.layers.Input(shape=(1,), dtype=tf.int32) tmp = tf.one_hot(model_in, NUM_STATES) tmp = tf.keras.layers.Dense(NUM_ACTIONS, ..

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