Programming Articles - Page 970 of 3363

To indicate if an interval is empty (contains no points), use the interval.is_empty property in Pandas. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([0, 0], [0, 0]) Display the interval −print("IntervalIndex...", interval)Check if the interval is empty −print("Is the interval empty?", interval.is_empty) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([0, 0], [0, 0]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # check if the interval is empty print("Is the interval empty?", interval.is_empty)OutputThis will produce the following output ... Read More

To get the length from the IntervalIndex, use the interval.length property in Pandas. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([10, 15, 20], [20, 25, 30]) Display the interval −print("IntervalIndex...", interval)Display the interval length −print("IntervalIndex length...", interval.length) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([10, 15, 20], [20, 25, 30]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # return the midpoint of the Interval print("The midpoint for the Interval...", interval.mid)OutputThis will produce the following output −IntervalIndex... IntervalIndex([(10, ... Read More

To get the midpoint from the IntervalIndex, use the interval.mid property in Pandas. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([10, 15, 20], [20, 25, 30]) Display the interval −print("IntervalIndex...", interval)Return the midpoint of the Interval −print("The midpoint for the Interval...", interval.mid) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([10, 15, 20], [20, 25, 30]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # Check whether the IntervalIndex is closed on the left-side, right-side, both or neither print("Checking ... Read More

To get the right bound for the IntervalIndex, use the interval.right property in Pandas. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([5, 10, 15], [15, 20, 25]) Display the interval −print("IntervalIndex...", interval)Get the right bound −print("The right bound for the IntervalIndex...", interval.right) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([5, 10, 15], [15, 20, 25]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # Check whether the IntervalIndex is closed on the left-side, right-side, both or neither print("Checking ... Read More

To get the left bound for the IntervalIndex, use the interval.left property in Pandas. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([5, 10, 15], [15, 20, 25]) Display the interval −print("IntervalIndex...", interval)Get the left bound −print("The left bound for the IntervalIndex...", interval.left) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([5, 10, 15], [15, 20, 25]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # Check whether the IntervalIndex is closed on the left-side, right-side, both or neither print("Checking ... Read More

To check whether the IntervalIndex intervals are closed on the left-side, right-side, both or neither, use the interval.closed property.At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([5, 10, 15], [15, 20, 25]) Display the interval −print("IntervalIndex...", interval)Check whether the IntervalIndex is closed on the left-side, right-side, both or neither −print("Checking for the type of IntervalIndex...", interval.closed) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([5, 10, 15], [15, 20, 25]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # Check ... Read More

To create an IntervalIndex in Pandas, use the pandas.IntervalIndex.from_arrays() method. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_arrays([5, 10, 15], [10, 15, 20]) Display the interval −print("IntervalIndex...",interval)ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_arrays([5, 10, 15], [10, 15, 20]) # display the interval print("IntervalIndex...",interval) # display the interval length print("IntervalIndex length...",interval.length)OutputThis will produce the following output −IntervalIndex... IntervalIndex([(5, 10], (10, 15], (15, 20]], dtype='interval[int64, right]') IntervalIndex length... Int64Index([5, 5, 5], dtype='int64')

To determine if two CategoricalIndex objects contain the same elements, use the equals() method. At first, import the required libraries −import pandas as pdSet the categories for the categorical using the "categories" parameter. Treat the categorical as ordered using the "ordered" parameter. Create two CategoricalIndex objects −catIndex1 = pd.CategoricalIndex(["p", "q", "r", "s", "p", "q", "r", "s"], ordered=True, categories=["p", "q", "r", "s"]) catIndex2 = pd.CategoricalIndex(["p", "q", "r", "s", "p", "q", "r", "s"], ordered=True, categories=["p", "q", "r", "s"])Check both the CategoricalIndex objects for equality −print("Check both the CategoricalIndex objects for equality...", catIndex1.equals(catIndex2))ExampleFollowing is the code −import pandas as pd # Set ... Read More

To Map values using input correspondence like a dict, use the CategoricalIndex.map() method in Pandas. At first, import the required libraries −import pandas as pdSet the categories for the categorical using the "categories" parameter. Treat the categorical as ordered using the "ordered" parameter −catIndex = pd.CategoricalIndex(["P", "Q", "R", "S", "P", "Q", "R", "S"], ordered=True, categories=["P", "Q", "R", "S"])Display the CategoricalIndex −print("CategoricalIndex...", catIndex) Map categories −print("CategoricalIndex after mapping...", catIndex.map({'P': 5, 'Q': 10, 'R': 15, 'S': 20}))ExampleFollowing is the code −import pandas as pd # Set the categories for the categorical using the "categories" parameter # Treat the categorical as ordered ... Read More

To set the categories of the CategoricalIndex to be ordered, use the as_ordered() method in Pandas.At first, import the required libraries −import pandas as pdSet the categories for the categorical using the "categories" parameter −catIndex = pd.CategoricalIndex(["p", "q", "r", "s", "p", "q", "r", "s"], categories=["p", "q", "r", "s"])Get the categories −print("Displaying Categories from CategoricalIndex...", catIndex.categories) Set the categories to be ordered −print("CategoricalIndex ordered...", catIndex.as_ordered())ExampleFollowing is the code −import pandas as pd # Set the categories for the categorical using the "categories" parameter catIndex = pd.CategoricalIndex(["p", "q", "r", "s", "p", "q", "r", "s"], categories=["p", "q", "r", "s"]) # Display ... Read More