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Create a recarray from a list of records in text form in Numpy
To create a recarray from a list of records in text form, use the numpy.core.records.fromrecords() method in Python Numpy. The names is set using the "names" parameter. The field names, either specified as a comma-separated string in the form 'col1, col2, col3', or as a list or tuple of strings in the form ['col1', 'col2', 'col3']. An empty list can be used, in that case default field names (‘f0’, ‘f1’, …) are used.
The first parameter is the data in the same field may be heterogeneous - they will be promoted to the highest data type. The dtype is the valid dtype for all arrays. The formats, names, titles, aligned, byteorder parameters, f dtype is None, these arguments are passed to numpy.format_parser to construct a dtype. If both formats and dtype are None, then this will auto-detect formats. Use list of tuples rather than list of lists for faster processing.
Steps
At first, import the required library −
import numpy as np
Create a new array using the numpy.array() method −
arr1 = np.array([[7, 14, 21], [30, 37, 45]]) arr2 = np.array([[11, 18, 24], [87.5, 65, 23.8]]) arr3 = np.array([['12', 'bbb', 'john'], ['5.6', '29', 'k']])
Display the arrays −
print("Array1...
",arr1)
print("Array2...
",arr2)
print("Array3...
",arr3)Get the type of the arrays −
print("
Array1 type...
", arr1.dtype)
print("
Array2 type...
", arr2.dtype)
print("
Array3 type...
", arr3.dtype)Get the dimensions of the Arrays −
print("
Array1 Dimensions...
", arr1.ndim)
print("
Array2 Dimensions...
", arr2.ndim)
print("
Array3 Dimensions...
", arr3.ndim)To create a recarray from a list of records in text form, use the numpy.core.records.fromrecords() method in Python Numpy −
print("
Record Array...
",np.core.records.fromrecords([arr1,arr2,arr3], names = 'col1, col2, col3'))Example
import numpy as np
# Create a new array using the numpy.array() method
arr1 = np.array([[7, 14, 21], [30, 37, 45]])
arr2 = np.array([[11, 18, 24], [87.5, 65, 23.8]])
arr3 = np.array([['12', 'bbb', 'john'], ['5.6', '29', 'k']])
# Display the arrays
print("Array1...
",arr1)
print("Array2...
",arr2)
print("Array3...
",arr3)
# Get the type of the arrays
print("
Array1 type...
", arr1.dtype)
print("
Array2 type...
", arr2.dtype)
print("
Array3 type...
", arr3.dtype)
# Get the dimensions of the Arrays
print("
Array1 Dimensions...
", arr1.ndim)
print("
Array2 Dimensions...
", arr2.ndim)
print("
Array3 Dimensions...
", arr3.ndim)
# To create a recarray from a list of records in text form, use the numpy.core.records.fromrecords() method in Python Numpy
# The names is set using the "names" parameter
# The field names, either specified as a comma-separated string in the form 'col1, col2, col3', or as a list or tuple of strings in the form ['col1', 'col2', 'col3'].
# An empty list can be used, in that case default field names (‘f0’, ‘f1’, …) are used.
print("
Record Array...
",np.core.records.fromrecords([arr1,arr2,arr3], names = 'col1, col2, col3'))Output
Array1...
[[ 7 14 21]
[30 37 45]]
Array2...
[[11. 18. 24. ]
[87.5 65. 23.8]]
Array3...
[['12' 'bbb' 'john']
['5.6' '29' 'k']]
Array1 type...
int64
Array2 type...
float64
Array3 type...
<U4
Array1 Dimensions...
2
Array2 Dimensions...
2
Array3 Dimensions...
2
Record Array...
[[('7', '14', '21') ('30', '37', '45')]
[('11.0', '18.0', '24.0') ('87.5', '65.0', '23.8')]
[('12', 'bbb', 'john') ('5.6', '29', 'k')]]
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