The code ran fine 2 weeks back, but I am having trouble now.ĭo you think its tensorflow or keras versions?įile "D:\JetBrains\Toolbox\apps\P圜harm-P\ch-0\201.6668.115\plugins\python\helpers\pydev\pydevd.py", line 1438, in _exec I am trying to run the code as is but getting this error. ValueError: setting an array element with a sequence. ![]() > 85 return array(a, dtype, copy=False, order=order) ~/anaconda3/lib/python3.6/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order) > 3277 dtype=tensor_type.as_numpy_dtype)) ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/keras/backend.py in call(self, inputs)ģ275 tensor_type = dtypes_module.as_dtype(tensor.dtype) ~/anaconda3/lib/python3.6/site-packages/keras/engine/training_arrays.py in fit_loop(model, fit_function, fit_inputs, out_labels, batch_size, epochs, verbose, callbacks, val_function, val_inputs, shuffle, initial_epoch, steps_per_epoch, validation_steps, validation_freq)ġ94 ins_batch = ins_batch.toarray() ~/anaconda3/lib/python3.6/site-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs) ValueError Traceback (most recent call last) Please use tf.compat.v1.global_variables instead. WARNING:tensorflow:From /Users/manohar/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:422: The name tf.global_variables is deprecated. If you have a list of lists that you want to convert to a DataFrame, you can use the pd.DataFrame constructor to create a new DataFrame from the list of lists.Dataset has 2708 nodes, 5429 edges, 1433 features. To fix the error, you can use the at or iat accessor methods to assign a scalar value to a single cell of the column, or you can use the pd.Series constructor to create a new column from a list or an array. In most cases, the error occurs when you try to assign a list or an array to a DataFrame column that expects a scalar value. The ValueError: setting an array element with a sequence error can be frustrating to deal with, but it is usually easy to fix once you understand what is causing it. This will create a new DataFrame with the values: a b cīe aware that if your list of lists contains mixed data types (such as numeric and string values), Pandas will convert all the values to a common data type. Import pandas as pd data =, , ] df = pd. ![]() This can happen when you try to assign a list or an array to a single cell of a DataFrame column, or when you try to assign a list or an array to an entire column.įor example, consider the following code: ![]() The ValueError: setting an array element with a sequence error occurs when you try to assign a sequence (such as a list or an array) to a Pandas DataFrame column that expects a scalar value. What is the “ValueError: setting an array element with a sequence” error? We assume that you have a basic knowledge of Pandas and Python. In this article, we will explain what this error message means and provide some tips on how to fix it. This error message can be frustrating, especially if you don’t know what it means or how to fix it. If you have been working with Pandas for a while, you have probably come across the ValueError: setting an array element with a sequence error at some point. ![]() | Miscellaneous How to Fix “ValueError: setting an array element with a sequence” for Pandas
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