如何用 Python 从字典中创建 data frame-Pandas？
原文:https://www.geeksforgeeks.org/如何从 python 字典创建数据框架-pandas/
让我们讨论一下如何从熊猫的字典中创建数据帧。有多种方法可以完成这项任务。
方法 1: 使用熊猫的默认构造函数从字典中创建数据帧。Dataframe 类。
代码:
# import pandas library
import pandas as pd
# dictionary with list object in values
details = {
'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
'Age' : [23, 21, 22, 21],
'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
# creating a Dataframe object
df = pd.DataFrame(details)
df
输出:
方法 2: 使用用户定义的索引从字典创建数据帧。
代码:
# import pandas library
import pandas as pd
# dictionary with list object in values
details = {
'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
'Age' : [23, 21, 22, 21],
'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
# creating a Dataframe object from dictionary
# with custom indexing
df = pd.DataFrame(details, index = ['a', 'b', 'c', 'd'])
df
输出:
方法 3: 从简单字典创建数据帧，即带有关键字和简单值(如整数值或字符串值)的字典。
代码:
# import pandas library
import pandas as pd
# dictionary
details = {
'Ankit' : 22,
'Golu' : 21,
'hacker' : 23
}
# creating a Dataframe object from a list
# of tuples of key, value pair
df = pd.DataFrame(list(details.items()))
df
输出:
方法 4: 从字典中创建仅包含所需列的数据框。
代码:
# import pandas library
import pandas as pd
# dictionary with list object in values
details = {
'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
'Age' : [23, 21, 22, 21],
'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
# creating a Dataframe object with skipping
# one column i.e skipping age column.
df = pd.DataFrame(details, columns = ['Name', 'University'])
df
输出:
方法 5: 从不同方向的字典中创建数据帧，即字典键作为数据帧中的索引。
代码:
# import pandas library
import pandas as pd
# dictionary with list object in values
details = {
'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
'Age' : [23, 21, 22, 21],
'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
# creating a Dataframe object in which dictionary
# key is act as index value and column value is
# 0, 1, 2...
df = pd.DataFrame.from_dict(details, orient = 'index')
df
输出:
方法 6: 从嵌套字典创建数据帧。
代码:
# import pandas library
import pandas as pd
# dictionary with dictionary object
# in values i.e. nested dictionary
details = {
0 : {
'Name' : 'Ankit',
'Age' : 22,
'University' : 'BHU'
},
1 : {
'Name' : 'Aishwarya',
'Age' : 21,
'University' : 'JNU'
},
2 : {
'Name' : 'Shaurya',
'Age' : 23,
'University' : 'DU'
}
}
# creating a Dataframe object
# from nested dictionary
# in which inside dictionary
# key is act as index value
# and column value is 0, 1, 2...
df = pd.DataFrame(details)
# swap the columns with indexes
df = df.transpose()
df
输出:
