在Python Pandas中查找某一列的指数
让我们看看如何在Pandas Dataframe中找到一个列的指数。首先,让我们创建一个Dataframe。
# importing pandas and
# numpy libraries
import pandas as pd
import numpy as np
# creating and initializing a list
values= [ ['Rohan', 5, 50.59], ['Elvish', 2, 90.57],
['Deepak', 10, 98.51], ['Soni', 4, 40.24],
['Radhika', 1, 99.05], ['Vansh', 15, 85.56] ]
# creating a pandas dataframe
df = pd.DataFrame(values, columns = ['Name',
'University_Rank',
'University_Marks'])
# displaying the data frame
df
输出:
通过使用numpy.exp()函数可以找出任何列的指数。这个函数计算输入数组/系列的指数。
语法: numpy.exp(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None)
返回:一个包含输入数组/系列所有元素的指数的数组。
例子1:寻找单列的指数(整数值)。
# importing pandas and
# numpy libraries
import pandas as pd
import numpy as np
# creating and initializing a list
values= [ ['Rohan', 5, 50.59], ['Elvish', 2, 90.57],
['Deepak', 10, 98.51], ['Soni', 4, 40.24],
['Radhika', 1, 99.05], ['Vansh', 15, 85.56] ]
# creating a pandas dataframe
df = pd.DataFrame(values, columns = ['Name',
'University_Rank',
'University_Marks'])
# finding the exponential value
# of column using np.exp() function
df['exp_value'] = np.exp(df['University_Rank'])
# displaying the data frame
df
输出:
例子2:寻找单列的指数(浮点数)。
# importing pandas and
# numpy libraries
import pandas as pd
import numpy as np
# creating and initializing a list
values= [ ['Rohan', 5, 50.59], ['Elvish', 2, 90.57],
['Deepak', 10, 98.51], ['Soni', 4, 40.24],
['Radhika', 1, 99.05], ['Vansh', 15, 85.56] ]
# creating a pandas dataframe
df = pd.DataFrame(values, columns = ['Name',
'University_Rank',
'University_Marks'])
# finding the exponential value
# of column using np.exp() function
df['exp_value'] = np.exp(df['University_Marks'])
# displaying the data frame
df
输出: