Intervals에 값이 포함되어 있는지 요소별로 확인하려면 array.contains()를 사용하세요. 방법.
먼저 필요한 라이브러리를 가져옵니다 -
import pandas as pd
배열과 유사한 분할에서 새 IntervalArray를 구성하십시오. -
array = pd.arrays.IntervalArray.from_breaks([0, 1, 2, 3, 4, 5])
간격 표시 -
print("Our IntervalArray...\n",array)
간격에 특정 값이 포함되어 있는지 확인 -
print("\nDoes the Intervals contain the value? \n",array.contains(3.5))
예
다음은 코드입니다 -
import pandas as pd # Construct a new IntervalArray from an array-like of splits array = pd.arrays.IntervalArray.from_breaks([0, 1, 2, 3, 4, 5]) # Display the IntervalArray print("Our IntervalArray...\n",array) # Getting the length of IntervalArray # Returns an Index with entries denoting the length of each Interval in the IntervalArray print("\nOur IntervalArray length...\n",array.length) # midpoint of each Interval in the IntervalArray as an Index print("\nThe midpoint of each interval in the IntervalArray...\n",array.mid) # get the right endpoints print("\nThe right endpoints of each Interval in the IntervalArray as an Index...\n",array.right) print("\nDoes the Intervals contain the value? \n",array.contains(3.5))
출력
이것은 다음 코드를 생성합니다 -
Our IntervalArray... <IntervalArray> [(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]] Length: 5, dtype: interval[int64, right] Our IntervalArray length... Int64Index([1, 1, 1, 1, 1], dtype='int64') The midpoint of each interval in the IntervalArray... Float64Index([0.5, 1.5, 2.5, 3.5, 4.5], dtype='float64') The right endpoints of each Interval in the IntervalArray as an Index... Int64Index([1, 2, 3, 4, 5], dtype='int64') Does the Intervals contain the value? [False False False True False]