如何在 Python-Pandas 中逐元素获取数组值的权力?
让我们看看如何按元素获取数组值的幂。 Dataframe/Series.pow()用于计算元素本身或提供的其他系列的功率。此函数仅适用于实数,不给出复数的结果。
那么让我们看看这些程序:
示例 1:将一维数组映射到具有默认数字索引或自定义索引的 pandas 系列然后将相应的元素提升到自己的幂。
Python3
# import required modules
import numpy as np
import pandas as pd
# create an array
sample_array = np.array([1, 2, 3])
# uni dimensional arrays can be
# mapped to pandas series
sr = pd.Series(sample_array)
print ("Original Array :")
print (sr)
# calculating element-wise power
power_array = sr.pow(sr)
print ("Element-wise power array")
print (power_array)
Python3
# module to work with arrays in python
import array
# module required to compute power
import pandas as pd
# creating a 1-dimensional floating
# point array containing three elements
sample_array = array.array('d',
[1.1, 2.0, 3.5])
# uni dimensional arrays can
# be mapped to pandas series
sr = pd.Series(sample_array)
print ("Original Array :")
print (sr)
# computing power of each
# element with itself
power_array = sr.pow(sr)
print ("Element-wise power array")
print (power_array)
Python3
# module to work with
# arrays in python
import array
# module required to
# compute power
import pandas as pd
# 2-d matrix containing
# 2 rows and 3 columns
df = pd.DataFrame({'X': [1,2],
'Y': [3,4],
'Z': [5,6]});
print ("Original Array :")
print(df)
# power function to calculate
# power of data frame elements
# with itself
power_array = df.pow(df)
print ("Element-wise power array")
print (power_array)
输出:
示例 2:也可以计算浮点十进制数的幂。
Python3
# module to work with arrays in python
import array
# module required to compute power
import pandas as pd
# creating a 1-dimensional floating
# point array containing three elements
sample_array = array.array('d',
[1.1, 2.0, 3.5])
# uni dimensional arrays can
# be mapped to pandas series
sr = pd.Series(sample_array)
print ("Original Array :")
print (sr)
# computing power of each
# element with itself
power_array = sr.pow(sr)
print ("Element-wise power array")
print (power_array)
输出:
示例 3: 多维数组可以映射到 pandas 数据帧。然后,数据框包含每个包含数字(整数或浮点数)的单元格,可以将其提升到自己的单独幂。
Python3
# module to work with
# arrays in python
import array
# module required to
# compute power
import pandas as pd
# 2-d matrix containing
# 2 rows and 3 columns
df = pd.DataFrame({'X': [1,2],
'Y': [3,4],
'Z': [5,6]});
print ("Original Array :")
print(df)
# power function to calculate
# power of data frame elements
# with itself
power_array = df.pow(df)
print ("Element-wise power array")
print (power_array)
输出: