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法律研究Python Pandas - 按元素检查区间元素中是否包含该值
若要按元素检查区间元素中是否包含该值，请使用 array.contains() 方法。
首先，导入所需的库 −
import pandas as pd
从分裂数组类似存储中构建一个新的 IntervalArray −
array = pd.arrays.IntervalArray.from_breaks([0, 1, 2, 3, 4, 5])
显示区间 −
print("Our IntervalArray...\n",array)检查 Interval 是否包含特定值 −
print("\nDoes the Intervals contain the value? \n",array.contains(3.5))
示例
以下为代码 −
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))输出
这将生成以下代码 −
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]
更新于： 2021 年 10 月 13 日
494 次浏览
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