Overview:
- Elements of one pandas Series object can be compared with the corresponding elements of another pandas Series object, and checked whether the first element is greater than the second.
- The results are returned as a separate pandas Series, consisting of test results as Boolean values - True and False.
Example:
- The following Python program uses numpy to generate a sample of ten random floating-point numbers and a sample of ten integers.
- These samples(ndarray objects) are loaded into pandas Series objects and checked whether the elements from the floating-point Series is greater than the elements from the integer Series. The resultant Series with Boolean values is printed onto the console.
|
# Example program to check whether each element of a pandas Series # is greater than the corresponding element from another pandas Series import pandas as pds import numpy as np
# Generate random floating point numbers fractions = 4 * np.random.random_sample(10);
# Generate random integers integers = np.random.randint(10, size=10);
# Load the floats into a pandas Series series1 = pds.Series(fractions); series2 = pds.Series(integers);
# Check whether each element of series1 is greater than # the corresponding element from series2 series3 = series1.gt(series2);
print("Series of floating point numbers:"); print(series1);
print("Series of integers:"); print(series2);
print("Result of applying the greater than function(gt):"); print(series3); |
Output:
|
Series of floating point numbers: 0 0.617934 1 3.462905 2 0.283336 3 1.708910 4 0.741405 5 1.742751 6 3.657854 7 0.137984 8 3.203777 9 3.666683 dtype: float64 Series of integers: 0 8 1 6 2 3 3 4 4 9 5 3 6 2 7 0 8 1 9 7 dtype: int64 Result of applying the greater than function(gt): 0 False 1 False 2 False 3 False 4 False 5 False 6 True 7 True 8 True 9 False dtype: bool |