data['new_column'] = data['string_column'].str.contains('substring') 其中,'new_column'是新列的名称,'string_column'是包含字符串的列的名称,'substring'是要检查的子字符串。 查看结果:可以使用head()函数查看新列的前几行,以确保新列已成功创建。
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...
将Excel 文件写入内存 pandas 支持将 Excel 文件写入类似缓冲区的对象,如StringIO或BytesIO,使用ExcelWriter。 from io import BytesIObio = BytesIO()# By setting the 'engine' in the ExcelWriter constructor.writer = pd.ExcelWriter(bio, engine="xlsxwriter")df.to_excel(writer, sheet_name="Sheet1")...
fromsqlalchemyimportcreate_engineimportpolarsaspl query ="SELECT * FROM user_to_role"engine = create_engine("mysql+pymysql://")# 这里我们将 user_id 改成了字符串,当然我们改成字符串反而是不对的,这里只是演示这个功能df = pl.read_database(query, engine, schema_overrides={"user_id": pl.Str...
..: dtype="string").str.contains(pattern) ...: Out[127]: 0 False 1 False 2 True 3 True 4 True 5 True dtype: boolean 代码语言:javascript 代码运行次数:0 运行 AI代码解释 In [128]: pd.Series(['1', '2', '3a', '3b', '03c', '4dx'], ...: dtype="string").str.match(...
`pandas.arrays.StringArray` or:class:`pandas.arrays.ArrowStringArray`:class:`bool` :class:`pandas.arrays.BooleanArray`===The ExtensionArray created when the scalar type is :class:`str` is determined by``pd.options.mode.string_storage`` if the dtype is not explicitly given.For all other ca...
lsuffix:代表如果df和other有重名的columnname,则增加后缀在df rsuffix:代表如果df和other有重名的columnname,则增加后缀在other 七、操作字符串 1.是否包含 obj.str.contains('str1'): 返回一个bool类型,如果包含str1返回True,否则返回False 2.查找 obj.str.findall(pattern,flags=re.IGNORECASE) pattern:正则表...
可以使用NamedAgg来完成列的命名 iris_gb.agg( sepal_min=pd.NamedAgg(column="sepal length (cm)", aggfunc="min"), sepal_max=pd.NamedAgg(column="sepal length (cm)", aggfunc="max"), petal_mean=pd.NamedAgg(column="petal length (cm)", aggfunc="mean"), petal_std=pd.NamedAgg(column="...
DF= DF.drop('column_name', 1); DF.drop('column_name',axis=1, inplace=True) DF.drop([DF.columns[[0,1, 3]]], axis=1,inplace=True) 抽样 re = train.sample(frac=0.25, random_state=66) 利用sql执行DF from pandasql import sqldf ...
Given a DataFrame, we need to convert a column value which is not of string type into string data type. By Pranit Sharma Last updated : September 20, 2023 A string is a group of characters. A string can contains any type of character including numerical characters, alphabetical characters...