To round the DateTimeIndex with hourly frequency, use the DateTimeIndex.round() method. For hourly frequency, use the freq parameter with value ‘H’.At first, import the required libraries −import pandas as pdCreate a DatetimeIndex with period 5 and frequency as T i.e. minutes −datetimeindex = pd.date_range('2021-09-29 07:00', periods=5, tz='Australia/Adelaide', freq='35T') Display DateTimeIndex −print("DateTimeIndex...", datetimeindex)Round operation on DateTimeIndex date with hourly frequency. For hourly frequency, we have used 'H' −print("Performing round operation with hourly frequency...", datetimeindex.round(freq='H'))ExampleFollowing is the code −import pandas as pd # DatetimeIndex with period 5 and frequency as T i.e. minutes # timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-09-29 07:00', periods=5, ... Read More

Suppose we have a list called fruits and another two values k and cap. Where each fruits[i] has three values: [c, s, t], this indicates fruit i costs c each, size of each of them is s, and there is total t of them. The k represents number of fruit baskets of capacity cap. We want to fill the fruit baskets with the following constraints in this order −Each basket can only hold same type fruitsEach basket should be as full as possibleEach basket should be as cheap as possibleSo we have to find the minimum cost required to fill ... Read More

To snap time stamps in DateTimeIndex to nearest occurring frequency, use the DateTimeIndex.snap() method. Set the frequency using the freq parameter.At first, import the required libraries −import pandas as pdCreate a DatetimeIndex with period 6 and frequency as D i.e. day −datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Adelaide', freq='D') Display DateTimeIndex −print("DateTimeIndex...", datetimeindex)Snap time stamps to nearest occurring i.e. Month end here −print("Snap time stamps to nearest occurring frequency...", datetimeindex.snap(freq='M'))ExampleFollowing is the code −import pandas as pd # DatetimeIndex with period 6 and frequency as D i.e. day # The timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Adelaide', freq='D') ... Read More

Suppose we have a list called costs. Where costs[i] has [c1, c2] indicates that for person i it costs c1 amount to reach city 0 and costs c2 amount to reach city 1. We want the same number of people to go to city 0 as city 1, we have to find the minimum cost required.So, if the input is like costs = [[2, 6], [10, 3], [4, 9], [5, 8]], then the output will be 17, because person 0 and 2 will go to city 0 and person 1 and 3 to city 1, so for city 0, the ... Read More

Suppose we have two numbers k and target. Now consider Amal and Bimal are playing a game. In each round Amal picks a number from 1 to k to add to the total score that initially starts from 0. Whoever crosses the total to target wins. Amal always plays first, we have to check whether he can force a win if both of them plays optimally.So, if the input is like k = 5 target = 10, then the output will be True, as if Amal picks 4 first, then whether Bimal picks 1, 2, ..., or 5, Amal can ... Read More

Suppose we have a list of numbers called nums. We have to find the index of every peak element in the nums, sorted in ascending order. An index i of a peak element when all of these three conditions are satisfied: 1. The next number on its right that's different than nums[i] doesn't present or must be smaller than nums[i] 2. The previous number on its left that's different than nums[i] doesn't present or must be smaller than nums[i] 3. There is at least one number on its left side or right side that is different from nums[i].So, if the ... Read More

To return an Index of formatted strings specified by date format, use the DateTimeIndex.strftime() method in Pandas.At first, import the required libraries −import pandas as pdCreate a DatetimeIndex with period 7 and frequency as D i.e. days −datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='2D') Display DateTimeIndex −print("DateTimeIndex...", datetimeindex)Formatted −print("Format with different directives...", datetimeindex.strftime('%b. %d, %Y was a %A'))ExampleFollowing is the code −import pandas as pd # DatetimeIndex with period 7 and frequency as D i.e. days # The timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='2D') # display DateTimeIndex print("DateTimeIndex...", datetimeindex) # display DateTimeIndex frequency ... Read More

To convert times to midnight in DateTimeIndex, use the DateTimeIndex.normalize() in Pandas.At first, import the required libraries −import pandas as pdCreate a DatetimeIndex with period 7 and frequency as H i.e. hours −datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='10H') Display DateTimeIndex −print("DateTimeIndex...", datetimeindex)The time component of the date-time is converted to midnight i.e. 00:00:00 −print("Normalize (converted the time component to midnight)...", datetimeindex.normalize())ExampleFollowing is the code −import pandas as pd # DatetimeIndex with period 7 and frequency as H i.e. hours # The timezone is Australia/Adelaide datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='10H') # display DateTimeIndex print("DateTimeIndex...", datetimeindex) ... Read More

To return index locations of values between particular time of day in DateTimeIndex, use the DateTimeIndex.indexer_between_time() method. Set the include_start parameter to True for including the start time.At first, import the required libraries −import pandas as pdCreate a DatetimeIndex with period 7 and frequency as T i.e. minutes −datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='20T') Display DateTimeIndex −print("DateTimeIndex...", datetimeindex)Display index locations of values between particular time of day. The "start_time" is set '02:30:50' and "end_time" '03:20:50'. Set include_start parameter to True −print("Index locations of values between particular time of day...", datetimeindex.indexer_between_time('03:10:50', '03:50:50', include_start = True))ExampleFollowing is the code −import pandas ... Read More

Suppose we have a list of numbers called nums. We have to find the sum of minimum of x for every sublist x in nums. If the answer is too large, then mod the result by 10^9 + 7.So, if the input is like nums = [5, 10, 20, 10, 0], then the output will be 90 because, the sublists are [[5], [10], [20], [10], [0], [5,10], [10,20], [20,10], [10,0], [5,10,20], [10,20,10], [20,10,0], [5,10,20,10], [10,20,10,0], [5,10,20,10,0]], and their minimum values are [5, 10, 20, 10, 0, 5, 10, 10, 0, 5, 10, 0, 5, 0, 0], so the sum is 90.To solve this, we will follow these steps −ans := 0s := a new listtemp_sum := 0for each index and value in nums, dowhile s and value