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如何在Python-Pandas中从字典中创建DataFrame
让我们来讨论如何在Pandas中从字典中创建DataFrame。有多种方法来完成这项任务。 方法1：使用pandas.Dataframe类的默认构造函数从字典中创建DataFrame。 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：用用户定义的索引从字典中创建DataFrame。 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：从简单的字典中创建DataFrame，即带有键和简单值的字典，如整数或字符串值。 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：从字典中只用所需的列来创建数据框架。 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：从字典中创建不同方向的数据框架，即字典中的键作为数据框架的索引。 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：从嵌套的字典中创建数据框架。 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:
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