Output.loc = ĭemo - In : output = pd. You can also specify the dtype while creating the DataFrame, Example - output = pd.DataFrame(data = ], columns=, index=,dtype=object) Array elements are numbered starting with zero, which may seem confusing at first but is an important detail for many programming languages. Output.loc = #Your listĭemo - In : output = pd.DataFrame(data = ], columns=, index=) In python Valueerror: Setting an Array Element with a Sequence means you are creating a NumPy array of different types of elements in it. A way to fix this would be to use a non-numeric dtype (like object) or so. 1 Answer Sorted by: 1 H is a numpy-array with dtypefloat as it's default. ValueError: setting an array element with a sequence. Then when you try to set a list as the value, it errors out, due to the dtype. One of the main causes for the ValueError: setting array element with a sequence is when you’re trying to insert arrays of different dimensions into a NumPy array. X_train, X_test, y_train, y_test = train_test_split(x, y, test_size = 0.If you really want to set a list as the value for the element, the issue is with the dtype of the column, when you create the DataFrame, the dtype gets inferred as float64, since it only contains numeric values. We can use the Enumerable.Repeat() method in the System.Linq namespace to generate a sequence of a repeated value and then convert the sequence back to the. Island = labelencoder_X.fit_transform(island) Specie = labelencoder_X.fit_transform(specie) If we make the length of both arrays equal, then there will be no error. Imp_frequent = SimpleImputer(missing_values=np.nan or ".", strategy='most_frequent')įlength = imp_mean.fit_transform(flength) This will throw valueerror setting array element with sequence, because we are asking numpy to create an array from the list which has elements of different dimensions 1,2 and 3,4,5. Imp_mean = SimpleImputer(missing_values=np.nan, strategy='mean') This will convert the sequence in column 'A' to a numpy array. Then, we create a sequence that we want to assign to the array. ValueError: setting an array element with a sequenceįrom sklearn.linear_model import LinearRegressionįrom sklearn.model_selection import train_test_splitįrom sklearn.preprocessing import StandardScaler, LabelEncoder The above exception was the direct cause of the following exception:įile "C:\Users\ronbe\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\linear_model\_base.py", line 662, in fitįile "C:\Users\ronbe\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\ base.py", line 581, in _validate_dataįile "C:\Users\ronbe\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils\ validation.py", line 964, in check_X_yįile "C:\Users\ronbe\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils\ validation.py", line 746, in check_arrayĪrray = np.asarray(array, order=order, dtype=dtype) the backing array merely setting the value of an element is not a structural. TypeError: float() argument must be a string or a real number, not 'list' As elements are added to an ArrayList, its capacity grows automatically. Of y to (n_samples, ), for example using ravel(). The detected shape was (6,) + inhomogeneous part. The requested array has an inhomogeneous shape after 1 dimensions. I tried few things but still gets this.Ĭ:\Users\ronbe\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\preprocessing\_label.py:115: DataConversionWarning: A column-vector y was passed when a 1d array was expected. ValueError: setting an array element with a sequence. Trying to do a multiple linear regression with my csc, but getting this weird error all the time. Full shape received: (32, 152, 100, 100) Call arguments received by layer 'sequential3' (type Sequential): inputstf.
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