11、数据抽样 # Randomly sample rows from a DataFramesampled_df= df.sample(n=2) 12、计算累加和 # Calculating cumulative sumdf['Cumulative_Sum'] = df['Values'].cumsum() 13、删除重复的数据 # Removing duplicate rowsdf.drop_duplicates(subset=['Column1'...
drop_duplates()可以使用这个方法删除重复的行。# Drop duplicate rows (but only keep the first row)df = df.drop_duplicates(keep='first') #keep='first' / keep='last' / keep=False# Note: inplace=True modifies the DataFrame rather than creating a new onedf.drop_duplicates(keep='first', i...
pandas去重函数 df.drop_duplicates? Signature:df.drop_duplicates(subset=None, keep='first', inplace=False) Docstring: Return DataFrame with duplicate rows removed, optionally only considering certain columns Parameters subset: column label or sequence of labels, optional Only consider certain columns for...
drop_duplates()可以使用这个方法删除重复的行。 代码语言:javascript 复制 # Drop duplicaterows(but only keep the first row)df=df.drop_duplicates(keep='first')#keep='first'/keep='last'/keep=False # Note:inplace=True modifies the DataFrame rather than creating anewonedf.drop_duplicates(keep='f...
pandas 可以利用PyArrow来扩展功能并改善各种 API 的性能。这包括: 与NumPy 相比,拥有更广泛的数据类型 对所有数据类型支持缺失数据(NA) 高性能 IO 读取器集成 便于与基于 Apache Arrow 规范的其他数据框架库(例如 polars、cuDF)进行互操作性 要使用此功能,请确保您已经安装了最低支持的 PyArrow 版本。 数据...
# Removing duplicate rows df.drop_duplicates(subset=['Column1', 'Column2'], keep='first', inplace=True) 14、创建虚拟变量 pandas.get_dummies() 是 Pandas 中用于执行独热编码(One-Hot Encoding)的函数。 # Creating dummy variables for categorical data ...
df2 = df.loc[:,~df.T.duplicated(keep='last')] # Example 6: Use DataFrame.columns.duplicated() # To drop duplicate columns duplicate_cols = df.columns[df.columns.duplicated()] df.drop(columns=duplicate_cols, inplace=True) Now, let’s create a DataFrame with a few duplicate rows and ...
DataFrame.drop_duplicates(self, subset=None, keep='first', inplace=False) Return DataFrame with duplicate rows removed, optiona
# Removing duplicate rows df.drop_duplicates(subset=['Column1', 'Column2'], keep='first'...
https://pandas.pydata.org/pandas-docs/version/0.22/generated/pandas.DataFrame.drop_duplicates.html DataFrame.drop_duplicates(subset=None, keep='first', inplace=False) grouped = grouped.drop_duplicates(['A', 'B']) Drop all duplicate rows in Python Pandas - Stack Overflow https://stackoverflo...