Pandas的索引对象负责管理轴标签和其他元数据,索引对象不能修改,否则会报错。也只有这样才能保证数据的准确性,并且保证索引对象在多个数据结构之间进行安全共享。 我们可以直接查看索引有哪些。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 df2=pd.DataFrame(data,columns=['city','year','name'],in
In [31]: df[["foo", "qux"]].columns.to_numpy() Out[31]: array([('foo', 'one'), ('foo', 'two'), ('qux', 'one'), ('qux', 'two')], dtype=object) # for a specific level In [32]: df[["foo", "qux"]].columns.get_level_values(0) Out[32]: Index(['foo', 'f...
df.info() # 查看索引、数据类型和内存信息 df.columns() # 查看字段()名称 df.describe() # 查看汇总统计 s.value_counts() # 统计某个值出现次数 df.apply(pd.Series.value_counts) # 查看DataFrame对象中每列的唯值和计数 df.isnull().any() # 查看是否有缺失值 df[df[column_name].duplicated()...
DataFrame'> RangeIndex: 3 entries, 0 to 2 Data columns (total 3 columns): # Column Non-Null Count Dtype --- --- --- --- 0 A 3 non-null int64 1 B 3 non-null object 2 C 3 non-null bool dtypes: bool(1), int64(1), object(1) memory usage: 251.0+ bytes describe() pd.de...
you can select specific columns before applying the function. For example,selected_col = [col1, col2] df[selected_col].apply(func, axis = 1) Howcan I use the apply function on a Series as well? Theapplyfunction can be used on both DataFrames and Series. When used on a Series, it...
apply()allows for the application of custom transformations to DataFrame rows or columns, enabling complex data manipulations tailored to specific needs. By returning multiple columns from the applied function,apply()facilitates the aggregation of data from multiple sources or the creation of derived fea...
6 rows x 16 columns] Another aggregation example is to compute the number of unique values of each group. This is similar to thevalue_countsfunction, except that it only counts unique values. In [77]: ll = [['foo', 1], ['foo', 2], ['foo', 2], ['bar', 1], ['bar', 1]...
(include=['int']).sum(1)df['total'] = df.loc[:,'Q1':'Q4'].apply(lambda x: sum(x), axis='columns') df.loc[:, 'Q10'] = '我是新来的' # 也可以 # 增加一列并赋值,不满足条件的为NaN df.loc[df.num >= 60, '成绩'] = '合格' df.loc[df.num < 60, '成绩'] = '不...
It shows that our example data consists of six rows and the three columns “x1”, “x2”, and “x3”.In addition, we have to create a list that we can add as a new column to our data set.new_col = ['a', 'b', 'c', 'd', 'e', 'f'] # Create example list print(new_...
How to find row where values for column is maximal in a Pandas DataFrame? How to apply Pandas function to column to create multiple new columns? How to convert Pandas DataFrame to list of Dictionaries? How to extract specific columns to new DataFrame?