序列(Series)最基本的选择是使用行标签来选择一个标量值,数据框(DataFrame)最基本的选择是使用列名获得一个序列。对于序列来说,如果行索引是整数,那么轴标签就是整数;对于数据框而言,列的标签通常都是文本类型。 创建一个数据框,用于数据演示: df = pd.DataFrame(np.random.randn(8, 4), columns=['A','B',...
fill_value=0) In [34]: dense.astype(dtype) Out[34]: A 0 1 1 0 2 0 3 1 ```## 与*scipy.sparse*的交互 使用`DataFrame.sparse.from_spmatrix()`从稀疏矩阵创建具有稀疏值的`DataFrame`。 `
In [1]: dates = pd.date_range('1/1/2000', periods=8) In [2]: df = pd.DataFrame(np.random.randn(8, 4), ...: index=dates, columns=['A', 'B', 'C', 'D']) ...: In [3]: df Out[3]: A B C D 2000-01-01 0.469112 -0.282863 -1.509059 -1.135632 2000-01-02 1.212112...
In [7]: df.info(memory_usage="deep") <class 'pandas.core.frame.DataFrame'> RangeIndex: 5000 entries, 0 to 4999 Data columns (total 8 columns): # Column Non-Null Count Dtype --- --- --- --- 0 int64 5000 non-null int64 1 float64 5000 non-null float64 2 datetime64[ns] 5000...
df["yWendu"] = df["yWendu"].str.replace("℃","").astype('int64')#DataFrame的排序df.sort_values(by="aqi") df.sort_values(by="aqi",ascending=False)#多列排序# 按空气质量等级、最高温度排序,默认升序df.sort_values(by=["aqiLevel","bWendu"])# 两个字段都是降序df.sort_values(by=[...
3.DataFrame的基本操作 3.1 数据修改 修改单个值:df.at[row_index, 'column_name'] = new_value 修改多个值:df.loc[row_indexer, 'column_name'] = new_value 或df.iloc[row_indexer, column_indexer] = new_value df = pd.DataFrame({'姓名':['abao','XQ','翔光','勍哥'],'科目':['语文'...
df=pd.DataFrame(data) # select all rows # and second to fourth column df[df.columns[1:4]] 输出: 方法#2:使用loc[] 示例1:选择两列 # Import pandas package importpandasaspd # Define a dictionary containing employee data data={'Name':['Jai','Princi','Gaurav','Anuj'], ...
您还可以使用pdi.sidebyside(obj1, obj2,…)并排显示多个Series或dataframe: pdi(代表pandas illustrated)是github上的一个开源库,具有本文所需的这个和其他功能。要使用它,就要写 pipinstallpandas-illustrated 索引(Index) 负责通过标签获取元素的对象称为index。它非常快:无论你有5行还是50亿行,你都可以在常量时间...
For the b value, we accept only the column names listed. Thus we get the following DataFrame: We can also slice the DataFrame created with the grades.csv file using the iloc[a,b] function, which only accepts integers for the a and b values. In this case, we can examine Sofia’s gra...
Pandas slice dataframe by multiple index ranges Pandas Extract Number from String Pandas groupby(), agg(): How to return results without the multi index? Convert Series of lists to one Series in Pandas How do I remove rows with duplicate values of columns in pandas dataframe?