可以使用布尔索引: # is the row not-NA in Name2? m1 = df['Name2'].notna() # is is the last row of a group? m2 = df['Name1'].notna().shift(-1, fill_value=True) # keep if either of the above condition is True out = df[m1|m2] Output: Name1 Name2 Name3 0 A1 B1 1...
DataFrame(mydata) df # 输出 Column1 Column2 0 1 a 1 2 b 2 3 c 指定行索引: # 指定行索引 df.index = ['row1', 'row2', 'row3'] df # 输出 Column1 Column2 row1 1 a row2 2 b row3 3 c 使用另一个 Series 或数组作为索引: # 使用另一个 Series 或数组作为索引 index_series =...
1. 查询是否存在空值 使用df.isnull()查看是否存在空值,此时会返回一个大小与表格大小相同的object,对应位置表示了表格中对应位置的空值情况,是True/False。如下图: 在数据量较大的情况下,这样的查询方式不够清晰,不能够帮助我们的判断。所以可以使用any()和all()函数来进行更易读的查询。其中any()函数如其名,...
Follow these steps to learn how to delete a column or a row from a DataFrame in the Pandas library of Python. Before we start: This Python tutorial is a part of our series of Python Package tutorials. The steps explained ahead are related to the sample project introduced here. You can ...
start=time.perf_counter()df=pd.DataFrame({"seq":[]})foriinrange(row_num):df.loc[i]=iend=...
我有一个大的数据集,我需要从pandas dataframe中删除一些重复项,但不是全部。在下面的示例数据中,每个产品记录都有产品名称、记录年份和参考号。在大多数情况下,一个产品应该只有一个参考号(最新的),但如果一个产品有多个相同的参考号,我需要保留这两个。
函数签名 DataFrame.to_excel(excel_writer,sheet_name='Sheet1',na_rep='',float_format=None,columns=None,header=True,index=True,index_label=None,startrow=0,startcol=0,engine='xlsxwriter',merge_cells=True,encoding=None,inf_rep='inf',verbose=False,freeze_panes=None) 参数详解 excel_writer:文件...
pandas按行按列遍历Dataframe的几种方式 遍历数据有以下三种方法: 简单对上面三种方法进行说明: iterrows(): 按行遍历,将DataFrame的每一行迭代为(index, Series)对,可以通过row[name]对元素进行访问。 itertuples(): 按行遍历,将DataFrame的每一行迭代为元祖,可以通过row[name]对元素进行访问,比iterrows()效率高...
df.info() <class 'pandas.core.frame.DataFrame'> RangeIndex: 6040 entries, 0 to 6039 Data columns (total 5 columns): UserID 6040 non-null int64 Gender 6040 non-null object Age 6040 non-null int64 Occupation 6040 non-null int64 Zip-code 6040 non-null object dtypes: int64(3), object(2...
We can also use the function to delete columns by applying some logic or based on some condition. We can use built-in as well as user-defined functions to drop columns. Drop all the columns usingloc If we want to drop all the columns from DataFrame we can easily do that usingDataFrame...