To count the unique values of each column of a dataframe, you can use the pandas dataframenunique()function. The following is the syntax: counts = df.nunique() Here,dfis the dataframe for which you want to know the unique counts. It returns a pandas Series of counts. By default, the...
我们可以使用 sys.getsizeof() 函数来证明这一点,首先查看单个的字符串,然后查看 pandas series 中的项。 fromsysimportgetsizeofs1='working out's2='memory usage for's3='strings in python is fun!'s4='strings in python is fun!'forsin[s1,s2,s3,s4]:print(getsizeof(s))---60657474 obj_series...
show() ## sns sns.pairplot(cars_df) 面板数据中的单变量画图,条形图/饼图: df['a'].value_counts(dropna=False) df.a.value_counts().plot(kind='bar', title = 'title', xlabel='Frequency') df.a.value_counts().plot(kind='pie') ## 类似于Series的画图。Values画图,index作为 x 轴的 ...
unique()) ['东莞' '深圳' '广州' '北京' '上海' '南京'] 六、查看数据表数值 import pandas as pd df = pd.DataFrame(pd.read_excel('test.xlsx', engine='openpyxl')) print(df.values) [[1001 Timestamp('2024-01-02 00:00:00') '东莞' '100-A' 23 1200.0] [1002 Timestamp('2024-01...
Series s.loc[indexer] DataFrame df.loc[row_indexer,column_indexer] 基础知识 如在上一节介绍数据结构时提到的,使用[](即__getitem__,对于熟悉在 Python 中实现类行为的人)进行索引的主要功能是选择较低维度的切片。以下表格显示了使用[]索引pandas 对象时的返回类型值: 对象类型 选择 返回值类型 Series seri...
要添加列,可以使用df['new_column'] = values的语法,其中df是DataFrame对象,new_column是要添加的新列的名称,values是要添加的新列的值。需要注意的是,values的长度必须与DataFrame的行数相匹配。 匹配索引是指根据索引值来进行数据的对齐。在Pandas中,DataFrame对象的索引可以是整数、标签或多级索引。当添加列时,...
AFTER: columnnamecan only be used as index because it's unique Set values according to criteria To set multiple cell values matching some criteria, usedf.loc[<row-index>,] = "some-value": Example: You want to setlives_in_calitoTruein all rows whosestateis"CA": importpandas...
notna() Finds values that are not not-a-number notnull() Finds values that are not NULL nsmallest() Sort the DataFrame by the specified columns, ascending, and return the specified number of rows nunique() Returns the number of unique values in the specified axis pct_change() Returns the...
sort_values astype resample shape to_xarray to_period kurt ffill idxmax plot to_clipboard cumsum nlargest var add abs any tshift nunique count combine keys values set_axis isnull sparse first_valid_index combine_first ewm notnull empty mask truncate to_csv bool at clip radd to_markdown ...
But what if you don’t have a single column that can do this? For example, you have the columns “name”, “age”, “address”, and “marks” in a DataFrame. Any of the above columns may not have unique values for all the different rows and are unfit as indexes. However, the ...