# In this program we are demonstrating how different
# Data-type can cause value error
 
import numpy
 
# Creating multi-dimension array
array1 = [1, 2, 4, [5, [6, 7]]]
 
# Data type of array element
Data_type = int
 
# This cause Value error
np_array = numpy.array(array1, dtype=Data_type)
 
print(np_array)

 File “C:\Users\computers\Downloads\he.py”, line 13, in <module>

 np_array = numpy.array(array1,dtype=Data_type);

ValueError: setting an array element with a sequence.

numpy.array( Array ,dtype = _**Common_DataType**_ );

# In this program we fix problem by different data-type
 
import numpy
 
# Creating multi-dimension array
array1 = [1, 2, 4, [5, [6, 7]]]
 
# Object Data type is accept all data-type
Data_type = object
 
# Now we fix the error
np_array = numpy.array(array1, dtype=Data_type)
 
print(np_array)

[1 2 4 list([5, [6, 7]])]

# In this program we are demonstrating how mismatch
# of data-type can cause value error
 
import numpy
 
# Creating array
array1 = ["Geeks", "For"]
 
# Default Data type of Array
Data_type = str
 
 
np_array = numpy.array(array1, dtype=Data_type)
# This cause error
np_array[1] = ["for", "Geeks"]
print(np_array)

if np_array.dtype == type( **Variable** ):
      expression;

# In this program we fix error by mismatch
# of data-type
 
import numpy
 
# Creating array
array1 = ["Geeks", "For"]
 
# Default Data type of Array
Data_type = str
 
 
np_array = numpy.array(array1, dtype=Data_type)
 
Variable = ["for", "Geeks"]
 
# First we match the data-type
if np_array.dtype == type(Variable):
    np_array[1] = Variable
else:
    print("Variable value is not the type of numpy array")
print(np_array)

Variable value is not the type of numpy array
['Geeks' 'For']