官方解释:https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop_duplicates.html#pandas.DataFrame.drop_duplicates DataFrame.drop_duplicates(subset=None, keep='first', inplace=False) Return DataFrame with duplicate rows removed, optionally only considering certain columns. #返回...
python drop_duplicate去除重复行 python # 导入pandas库 import pandas as pd # 读取csv文件 df = pd.read_csv('data.csv') # 去除重复行 df.drop_duplicates()发布于 3 月前 本站已为你智能检索到如下内容,以供参考: 🐻 相关问答 6 个 1、python数组去重,去除后面重复的,不改变原数组顺序 2、list中...
因此,我们可以创建一个新的数据集 df_less_missing_rows,该数据集删除了缺失值数量超过 35 的观察值。 # drop rows with a lot of missing values.ind_missing= df[df['num_missing'] >35].indexdf_less_missing_rows= df.drop(ind_missing, axis=0) 解决方案 2:丢弃特征 与解决方案 1 类似,我们只在...
我使用以下代码行de-duplicate: my_df = my_df.loc[(my_df["Col2"] != "") | ~my_df["Col1"].duplicated()] 这将删除Col1中具有重复项的一些但不是所有所需行。如果这样的“重复行”出现在应保留的行(作为non-empty Col2)之前,则不会删除该行,我的代码给出如下结果: Col1,Col2,Col3 A,rrr...
DataFrame.drop_duplicates([subset, keep, …]) Return DataFrame with duplicate rows removed, optionally only DataFrame.duplicated([subset, keep]) Return boolean Series denoting duplicate rows, optionally only DataFrame.equals(other) 两个数据框是否相同 ...
Bin edges must be unique和 You can drop duplicate edges by setting the ‘duplicates’ kwarg 1. 首先,报错如下: 然后,在qcut() 函数中设置duplicates参数为“drop”(不能设置为“raise”),解决(如下)。 本次纠错背景,来源于互金领域信用风控建模中的变量分箱处理。如下: ...
pandas 如何在python中删除_duplicates我认为您缺少drop_duplicates()中的列指示，请尝试使用like ...
DataFrame.drop(labels[, axis, level, …])返回删除的列 DataFrame.drop_duplicates([subset, keep, …])Return DataFrame with duplicate rows removed, optionally only DataFrame.duplicated([subset, keep])Return boolean Series denoting duplicate rows, optionally only ...
This also needs to be done as first step, in case we want to remove rows with inf values from a data set (more on that in Example 2). Have a look at the Python code and its output below: data_new1=data.copy()# Create duplicate of datadata_new1.replace([np.inf,- np.inf],np...
How to handle indexes on other axis (or axes).ignore_index : bool, default FalseIf True, 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 ...