DataFrame.drop(labels=None,axis=0,index=None,columns=None, inplace=False) 参数说明: labels 就是要删除的行列的名字,用列表给定 axis 默认为0,指删除行,因此删除columns时要指定axis=1; index 直接指定要删除的行 columns 直接指定要删除的列 inplace=False,默认该删除操作不改变原数据,而是返回一个执行删除...
df = pd.read_excel("test.xlsx", dtype=str, keep_default_na='') df.drop(columns=['寄件地区'], inplace=True) 5、列表头改名(补充) 如下:将某列表头【到件地区】修改为【对方地区】 df = pd.read_excel("test.xlsx", dtype=str, keep_default_na='') df = df.rename(columns={'到件地区...
do not use the index values along the concatenation axis. Theresulting axis will be labeled 0, ..., n - 1. This is useful if you areconcatenating objects where the concatenation axis does not havemeaningful indexing information. Note the index values on the otheraxes are still respected...
比如：如你所见，AND运算符会删除每一行中至少有一个值等于-1的记录。而OR运算符则要求两个值都等于-...
主要介绍drop函数,一般用不到删除这个方法,比如删除空值,参照前面索引空值即可。主要介绍drop函数,按照label进行就地删除。drop函数基本语法:Series.drop(labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise')。 series = pd.Series([10, 8, 9, 4, 4, 6, 8, 4]...
999 0.536671 0.674845 0.004224576 rows × 3 columnsmap映射¶映射就是指给一组数据中的每一个元素绑定一个固定的数据 In [283]: df = pd.read_csv('./data/map.csv').drop(columns='Unnamed: 0') dfOut[283]: namesalary 0 张三 10000 1 李四 15000 2 王五 21000 3 张三 10000In...
columns, df.dtypes): if "object" in str(j): dtypedict.update({i: String(64)}) if "float" in str(j): dtypedict.update({i: Float}) if "int" in str(j): dtypedict.update({i: Float}) return dtypedict 几个数据脱敏的样例: 姓名脱敏 代码语言:javascript 代码运行次数:0 运行 AI...
ri.drop('county_name', axis='columns', inplace=True) Powered By .dropna() Method The .dropna() method is a great way to drop rows based on the presence of missing values in that row. For example, using the dataset above, let's assume the stop_date and stop_time columns are cr...
validation.pyc in cross_validate(estimator, X, y, groups, scoring, cv, n_jobs, verbose, fit_params, pre_dispatch, return_train_score) 204 fit_params, return_train_score=return_train_score, 205 return_times=True) --> 206 for train, test in cv.split(X, y, groups)) 207 208 if ...
DataFrame size mutability:Columns can be added or removed from DataFrames or higher-dimensional data structures. Automated and explicit data alignment:pandas ensures data alignment by automatically aligning objects like Series and DataFrames to their labels, simplifying computations. ...