在熊猫-Python 中找到一列的指数
让我们看看如何在熊猫数据框中找到一列的指数。首先，让我们创建一个数据框架:
Python 3
# 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:
利用numpy . exp()函数求出任意一列的指数。该函数计算输入数组/序列的指数。
*语法:* numpy.exp(数组，out = None，其中= True，casting = 'same_kind '，order = 'K '，dtype = None)
*返回:*输入数组/序列中所有元素指数的数组。
*例 1:* 求单列的指数(整数值)。
Python 3
# 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 2:* 求单列的指数(浮点值)。
Python 3
# 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:*
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