在Pandas中,可以使用unique()方法来获取一个列中唯一值的数组。但是,如果要将一个不唯一的列变为唯一的列,可以按照以下步骤进行操作: 1. 使用duplicated()方法标记出重复的值:...
In case you want to know the count of each of the distinct values of a specific column, you can use the pandasvalue_counts()function. In the above dataframedf, if you want to know the count of each distinct value in the columnGender, you can use – # count of each unique value in...
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使用unique()方法获取唯一值列表,然后使用列表推导式创建新列: 代码语言:txt 复制 unique_values = df['column_name'].unique() df['new_column'] = [value for value in unique_values] 推荐的腾讯云相关产品:腾讯云数据库TDSQL,提供高性能、高可用的数据库服务。产品介绍链接:腾讯云数据库TDSQL 使用drop_duplic...
'value_2':values_2})df对year列进行唯一值计数：df.year.nunique()输出：10 对整个dataframe的每一个字段进行唯一值计数：df.nunique()3. infer_objects infer_objects用于将object类型列推断为更合适的数据类型。用法：# 直接将df或者series推断为合适的数据类型DataFrame.infer_objects()pandas支持多种数据类型...
unique_values = df['column_name'].unique() unique()函数会返回一个numpy数组,其中包含了所有去重之后的值。如果想要将该数组转换为列表,可以使用tolist()函数。例如: unique_values_list = df['column_name'].unique().tolist() 以上内容希望能对你有所帮助。
The unique value from the specified column has been returned in the output. We can also get distinct values from the multiple columns of Pandas DataFrame. Here is an example code: import pandas data1 = {'Name':["Anna","Joseph","Lily","Henry","Lily","Anna","Henry"],'Age' :[18,22...
pandas.unique(values) # or df['col'].unique() Note To work with pandas, we need to importpandaspackage first, below is the syntax: import pandas as pd Let us understand with the help of an example, Python program to find unique values from multiple columns ...
dataframe[‘column_name].unique() nunique():这个方法类似于unique,但它会返回唯一值的计数。 dataframe_name[‘column_name].nunique() info():此命令用于获取数据类型和列信息 columns:此命令用于显示数据框中存在的所有列名 示例: 1# importing pandas as pd for using data frame ...
a':'第一组','b':'第二组','c':'第一组','d':'第三组','e':'第二组'}by_column=...