Traceback (most recent call last): File "/Users/mhjensen/miniforge3/lib/python3.9/site-packages/jupyter_cache/executors/utils.py", line 58, in single_nb_execution executenb( File "/Users/mhjensen/miniforge3/lib/python3.9/site-packages/nbclient/client.py", line 1305, in execute return NotebookClient(nb=nb, resources=resources, km=km, **kwargs).execute() File "/Users/mhjensen/miniforge3/lib/python3.9/site-packages/jupyter_core/utils/__init__.py", line 166, in wrapped return loop.run_until_complete(inner) File "/Users/mhjensen/miniforge3/lib/python3.9/asyncio/base_events.py", line 647, in run_until_complete return future.result() File "/Users/mhjensen/miniforge3/lib/python3.9/site-packages/nbclient/client.py", line 705, in async_execute await self.async_execute_cell( File "/Users/mhjensen/miniforge3/lib/python3.9/site-packages/nbclient/client.py", line 1058, in async_execute_cell await self._check_raise_for_error(cell, cell_index, exec_reply) File "/Users/mhjensen/miniforge3/lib/python3.9/site-packages/nbclient/client.py", line 914, in _check_raise_for_error raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content) nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell: ------------------ %matplotlib inline # Start importing packages import pandas as pd import numpy as np import matplotlib.pyplot as plt import tensorflow as tf from tensorflow.keras import datasets, layers, models from tensorflow.keras.layers import Input from tensorflow.keras.models import Model, Sequential from tensorflow.keras.layers import Dense, SimpleRNN, LSTM, GRU from tensorflow.keras import optimizers from tensorflow.keras import regularizers from tensorflow.keras.utils import to_categorical # convert into dataset matrix def convertToMatrix(data, step): X, Y =[], [] for i in range(len(data)-step): d=i+step X.append(data[i:d,]) Y.append(data[d,]) return np.array(X), np.array(Y) step = 4 N = 1000 Tp = 800 t=np.arange(0,N) x=np.sin(0.02*t)+2*np.random.rand(N) df = pd.DataFrame(x) df.head() plt.plot(df) plt.show() values=df.values train,test = values[0:Tp,:], values[Tp:N,:] # add step elements into train and test test = np.append(test,np.repeat(test[-1,],step)) train = np.append(train,np.repeat(train[-1,],step)) trainX,trainY =convertToMatrix(train,step) testX,testY =convertToMatrix(test,step) trainX = np.reshape(trainX, (trainX.shape[0], 1, trainX.shape[1])) testX = np.reshape(testX, (testX.shape[0], 1, testX.shape[1])) model = Sequential() model.add(SimpleRNN(units=32, input_shape=(1,step), activation="relu")) model.add(Dense(8, activation="relu")) model.add(Dense(1)) model.compile(loss='mean_squared_error', optimizer='rmsprop') model.summary() model.fit(trainX,trainY, epochs=100, batch_size=16, verbose=2) trainPredict = model.predict(trainX) testPredict= model.predict(testX) predicted=np.concatenate((trainPredict,testPredict),axis=0) trainScore = model.evaluate(trainX, trainY, verbose=0) print(trainScore) index = df.index.values plt.plot(index,df) plt.plot(index,predicted) plt.axvline(df.index[Tp], c="r") plt.show() ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 1 ----> 1 get_ipython().run_line_magic('matplotlib', 'inline')  3 # Start importing packages  4 import pandas as pd File ~/miniforge3/lib/python3.9/site-packages/IPython/core/interactiveshell.py:2432, in InteractiveShell.run_line_magic(self, magic_name, line, _stack_depth)  2430 kwargs['local_ns'] = self.get_local_scope(stack_depth)  2431 with self.builtin_trap: -> 2432 result = fn(*args, **kwargs)  2434 # The code below prevents the output from being displayed  2435 # when using magics with decorator @output_can_be_silenced  2436 # when the last Python token in the expression is a ';'.  2437 if getattr(fn, magic.MAGIC_OUTPUT_CAN_BE_SILENCED, False): File ~/miniforge3/lib/python3.9/site-packages/IPython/core/magics/pylab.py:99, in PylabMagics.matplotlib(self, line)  97 print("Available matplotlib backends: %s" % backends_list)  98 else: ---> 99 gui, backend = self.shell.enable_matplotlib(args.gui.lower() if isinstance(args.gui, str) else args.gui)  100 self._show_matplotlib_backend(args.gui, backend) File ~/miniforge3/lib/python3.9/site-packages/IPython/core/interactiveshell.py:3606, in InteractiveShell.enable_matplotlib(self, gui)  3585 def enable_matplotlib(self, gui=None):  3586  """Enable interactive matplotlib and inline figure support.  3587  3588  This takes the following steps:  (...)  3604  display figures inline.  3605  """ -> 3606 from matplotlib_inline.backend_inline import configure_inline_support  3608 from IPython.core import pylabtools as pt  3609 gui, backend = pt.find_gui_and_backend(gui, self.pylab_gui_select) File ~/miniforge3/lib/python3.9/site-packages/matplotlib_inline/__init__.py:1 ----> 1 from . import backend_inline, config # noqa  2 __version__ = "0.1.6" # noqa File ~/miniforge3/lib/python3.9/site-packages/matplotlib_inline/backend_inline.py:6  1 """A matplotlib backend for publishing figures via display_data"""  3 # Copyright (c) IPython Development Team.  4 # Distributed under the terms of the BSD 3-Clause License. ----> 6 import matplotlib  7 from matplotlib import colors  8 from matplotlib.backends import backend_agg ModuleNotFoundError: No module named 'matplotlib'