cc_count+=1 df.loc[rowIndex]['Cli-Sub-Cat'] = 'Config' >>> Trying to insert a new column with a custom value continue if re.search('counter|stat', headline, re.I): counter_count+=1 df.loc[rowIndex]['Cli-Sub-Cat'] = 'Counter' continue if re.search('debug', headline, re....
填充值参数:value=None(空值) import pandas as pd def test(): # 读取Excel文件 df = pd.read_excel('测试数据.xlsx') # 插入列 df.insert(loc=2, column='爱好', value=None) # 保存修改后的DataFrame到新的Excel文件 df.to_excel('结果.xlsx', index=False) test() 3、插入多列 假设我需要在...
ExcelFile.parse(sheet_name=0, header=0, names=None, index_col=None, usecols=None, converters=None, true_values=None, false_values=None, skiprows=None, nrows=None, na_values=None, parse_dates=False, date_parser=_NoDefault.no_default, date_format=None, thousands=None, comment=None, skipfoo...
dtype: datetime64[ns] In [566]: store.select_column("df_dc", "string") Out[566]: 0 foo 1 foo 2 foo 3 foo 4 NaN 5 NaN 6 foo 7 bar Name: string, dtype: object
with index value as first element of the tuple.DataFrame.lookup(row_labels, col_labels)Label-based “fancy indexing” function for DataFrame.DataFrame.pop(item)返回删除的项目DataFrame.tail([n])返回最后n行DataFrame.xs(key[, axis, level, drop_level])Returns a cross-section (row(s) or column...
df.insert insert(loc, column, value, allow_duplicates=False) 参数: loc: int型,表示第几列;若在第一列插入数据,则 loc=0 column: 给插入的列取名,如 column='新的一列'value:数字,array,series等都可(可自己尝试) allow_duplicates: 是否允许列名重复,选择Ture表示允许新的列名与已存在的列名重复。
Series 结构,也称 Series 序列,是 Pandas 常用的数据结构之一,它是一种类似于一维数组的结构,由一组数据值(value)和一组标签组成,其中标签与数据值之间是一一对应的关系。 Series 可以保存任何数据类型,比如整数、字符串、浮点数、Python 对象等,它的标签默认为整数,从 0 开始依次递增。Series 的结构图,如下所示...
Pandas version checks I have checked that this issue has not already been reported. I have confirmed this bug exists on the latest version of pandas. I have confirmed this bug exists on the main branch of pandas. Reproducible Example imp...
print(df['Department'].value_counts()) # 分类计数 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 1.2 数据清洗与转换 数据清洗是数据分析的关键步骤: # 处理缺失值 df.loc[2, 'Age'] = np.nan df['Age'] = df['Age'].fillna(df['Age'].mean()) ...
The type of the key-value pairs can be customized with the parameters (see below). Parameters --- orient : str {'dict', 'list', 'series', 'split', 'records', 'index'} Determines the type of the values of the dictionary. - 'dict' (default) : dict like {column -> {index -...