Python Pandas - 检查元素是否包含值
要按元素检查Intervals是否包含该值，请使用该方法。array.contains()
首先，导入所需的库-
import pandas as pd
从类似数组的拆分构造一个新的IntervalArray-
array = pd.arrays.IntervalArray.from_breaks([0, 1, 2, 3, 4, 5])
显示间隔-
print("Our IntervalArray...\n",array)检查间隔是否包含特定值-
print("\nDoes the Intervals contain the value? \n",array.contains(3.5))示例
以下是代码-
import pandas as pd
#从类似数组的拆分构造一个新的IntervalArray
array = pd.arrays.IntervalArray.from_breaks([0, 1, 2, 3, 4, 5])
#显示间隔数组
print("Our IntervalArray...\n",array)
#获取IntervalArray的长度
#返回一个索引，其中的条目表示IntervalArray中每个Interval的长度
print("\nOur IntervalArray length...\n",array.length)
#IntervalArray中每个Interval的中点作为索引
print("\nThe midpoint of each interval in the IntervalArray...\n",array.mid)
#获得正确的端点
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))输出结果这将产生以下代码-
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]