从 Numpy 数组创建数据框，并指定索引列和列标题
让我们看看如何从 Numpy 数组创建一个数据帧。我们还将学习如何指定数据框的索引和列标题。
进场:
- 导入
Pandas和Numpy模块。 - 创建一个
Numpy数组。 - 为数据框创建索引值和列值列表。
- 创建数据帧。
- 显示数据框。
例 1 :
# importiong the modules
import pandas as pd
import numpy as np
# creating the Numpy array
array = np.array([[1, 1, 1], [2, 4, 8], [3, 9, 27],
[4, 16, 64], [5, 25, 125], [6, 36, 216],
[7, 49, 343]])
# creating a list of index names
index_values = ['first', 'second', 'third',
'fourth', 'fifth', 'sixth', 'seventh']
# creating a list of column names
column_values = ['number', 'squares', 'cubes']
# creating the dataframe
df = pd.DataFrame(data = array,
index = index_values,
columns = column_values)
# displaying the dataframe
print(df)
输出:
例 2 :
# importiong the modules
import pandas as pd
import numpy as np
# creating the Numpy array
array = np.array([['Aditya', 20], ['Samruddhi', 15],
['Rohan', 21], ['Anantha', 20],
['Abhinandan', 21]])
# creating a list of index names
index_values = ['A', 'B', 'C', 'D', 'E']
# creating a list of column names
column_values = ['Names', 'Age']
# creating the dataframe
df = pd.DataFrame(data = array,
index = index_values,
columns = column_values)
# displaying the dataframe
print(df)
输出:
例 3 :
# importiong the modules
import pandas as pd
import numpy as np
# creating the Numpy array
array = np.array([['CEO', 20, 5], ['CTO', 22, 4.5],
['CFO', 21, 3], ['CMO', 24, 2]])
# creating a list of index names
index_values = [1, 2, 3, 4]
# creating a list of column names
column_values = ['Names', 'Age',
'Net worth in Millions']
# creating the dataframe
df = pd.DataFrame(data = array,
index = index_values,
columns = column_values)
# displaying the dataframe
print(df)
输出:
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