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To extract hour from the DateTimeIndex with specific time series frequency, use the DateTimeIndex.hour property.At first, import the required libraries −import pandas as pdDatetimeIndex with period 6 and frequency as H i.e. hour. The timezone is Australia/Sydney −datetimeindex = pd.date_range('2021-10-20 02:35:55', periods=6, tz='Australia/Sydney', freq='H') Display DateTimeIndex −print("DateTimeIndex...", datetimeindex)Get the hour −print("Getting the hour..", datetimeindex.hour) ExampleFollowing is the code −import pandas as pd # DatetimeIndex with period 6 and frequency as H i.e. hour # The timezone is Australia/Sydney datetimeindex = pd.date_range('2021-10-20 02:35:55', periods=6, tz='Australia/Sydney', freq='H') # display DateTimeIndex print("DateTimeIndex...", datetimeindex) # display DateTimeIndex frequency print("DateTimeIndex frequency...", datetimeindex.freq) ... Read More
Suppose we have two numbers n and k. Here n represents the number of games we are going to play. We have to find in how many ways we can win k or fewer games consecutively. If the answer is too large then mod the result by 10^9 + 7.So, if the input is like n = 3 k = 2, then the output will be 7, as the possible ways in which we can win 2 or fewer times consecutively, are ["LLL", "WLL", "LWL", "LLW", "WWL", "LWW", "WLW"]To solve this, we will follow these steps −m := 1^9 + ... Read More
To return an IntervalArray identical to the current one but closed on the specified side, use the set_closed() method with parameter set as both.At first, import the required libraries −import pandas as pdCreate IntervalArray −index = pd.arrays.IntervalArray.from_breaks(range(6)) Display the interval −print("IntervalIndex...", index)Return an IntervalArray identical to the current one but closed on specified side i.e. "both" here −print("Result...", index.set_closed('both')) ExampleFollowing is the code −import pandas as pd # Create IntervalArray index = pd.arrays.IntervalArray.from_breaks(range(6)) # Display the interval print("IntervalIndex...", index) # Display the interval length print("IntervalIndex length...", index.length) # the left bound print("The left bound for the ... Read More
To return an IntervalArray identical to the current one but closed on the left side, use the set_closed() method with value left.At first, import the required libraries −import pandas as pdCreate IntervalArray −index = pd.arrays.IntervalArray.from_breaks(range(5))Display the interval −print("IntervalIndex...", index)Return an IntervalArray identical to the current one but closed on specified side i.e. "left" here −print("Result...", index.set_closed('left')) ExampleFollowing is the code −import pandas as pd # Create IntervalArray index = pd.arrays.IntervalArray.from_breaks(range(5)) # Display the interval print("IntervalIndex...", index) # Display the interval length print("IntervalIndex length...", index.length) # the left bound print("The left bound for the IntervalIndex...", index.left) ... Read More
To get the locations of all the relevant interval if a label is in several intervals, use the get_loc() method in Pandas.At first, import the required libraries −import pandas as pdCreate two Interval objects. Closed intervals set using the "closed" parameter with value "both"interval1 = pd.Interval(50, 75) interval2 = pd.Interval(75, 90) interval3 = pd.Interval(50, 90)Create IntervalIndex from the three intervals −index = pd.IntervalIndex([interval1, interval2, interval3]) Get the locations of all the relevant interval if a label is in several intervals −print("Get the locations of all the relevant interval...", index.get_loc(65))ExampleFollowing is the code −import pandas as pd # Create two ... Read More
To get integer location for requested label, use the get_loc() method in Pandas. At first, import the required libraries −import pandas as pdCreate two Interval objects. Closed intervals set using the "closed" parameter with value "both" −interval1 = pd.Interval(50, 75) interval2 = pd.Interval(75, 90)Create IntervalIndex from the two intervals −index = pd.IntervalIndex([interval1, interval2]) Get integer location for requested label −print("Integer location for requested label...", index.get_loc(75))ExampleFollowing is the code −import pandas as pd # Create two Interval objects # Closed intervals set using the "closed" parameter with value "both" interval1 = pd.Interval(50, 75) interval2 = pd.Interval(75, 90) # display ... Read More
To check if Intervals that only have an open endpoint in common overlap or not, use the IntervalIndex.is_overlapping property.At first, import the required libraries −import pandas as pdCreate IntervalIndex. The intervals are closed on the left-side since the "closed" parameter is set "left" −interval = pd.interval_range(0, 8, closed='left') Display the interval −print("IntervalIndex...", interval)Check if the Intervals that only have an open endpoint in common overlap or not −print("Does the Intervals that have an open endpoint overlap?", interval.is_overlapping)ExampleFollowing is the code −import pandas as pd # Create IntervalIndex # The intervals are closed on the left-side since the "closed" parameter ... Read More
To check if Intervals that share closed endpoints overlap, use the IntervalIndex.is_overlapping property. At first, import the required libraries −import pandas as pdCreate IntervalIndex. The intervals are closed on both the sides since the "closed" parameter is set "both" −interval = pd.interval_range(0, 8, closed='both') Display the interval −print("IntervalIndex...", interval)Check if the Intervals that share closed endpoints overlap −print("Does the Intervals that share closed endpoints overlap?", interval.is_overlapping)ExampleFollowing is the code −import pandas as pd # Create IntervalIndex # The intervals are closed on both the sides since the "closed" parameter is set "both" interval = pd.interval_range(0, 8, closed='both') # ... Read More
To check if the IntervalIndex has overlapping intervals, use the Intervalndex.is_overlapping property. At first, import the required libraries −import pandas as pdCreate IntervalIndex −interval = pd.IntervalIndex.from_tuples([(10, 20), (15, 25)]) Display the interval −print("IntervalIndex...", interval)Check if the interval is overlapping or not −print("Is the interval overlapping?", interval.is_overlapping) ExampleFollowing is the code −import pandas as pd # Create IntervalIndex interval = pd.IntervalIndex.from_tuples([(10, 20), (15, 25)]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex length...", interval.length) # Check if the interval is overlapping or not print("Is the interval overlapping?", interval.is_overlapping)OutputThis will produce the following output ... Read More
To check if an interval with missing values is empty or not, use the IntervalIndex.is_empty property. At first, import the required libraries −import pandas as pd import numpy as npCreate IntervalIndex with NaN values −interval = pd.IntervalIndex.from_arrays([np.nan, np.nan], [np.nan, np.nan]) Display the interval −print("IntervalIndex...", interval)Check if the interval that contains missing values is empty or not −print("Is the interval empty?", interval.is_empty) ExampleFollowing is the code −import pandas as pd import numpy as np # Create IntervalIndex with NaN values interval = pd.IntervalIndex.from_arrays([np.nan, np.nan], [np.nan, np.nan]) # Display the interval print("IntervalIndex...", interval) # Display the interval length print("IntervalIndex ... Read More