Boolean).n_unique()) print(out) import polars.selectors as cs out = df.select(cs.numeric() - cs.first()) print(out) out = df.select(cs.contains("rn"), cs.matches(".*_.*")) print(out) Functions 代码语言:javascript 代码运行次数:0 运行 AI代码解释 df = pl.DataFrame( { "nrs"...
print(unique_df) Output: x y 0 7 0 1 2 3 3 1 1 value_counts() method The count of each unique value in a DataFrame is returned by this method. In addition, this method can be used to determine a series object with the count of unique values in a definite column. Example: impor...
dataset's distribution, excluding ``NaN`` values. Analyzes both numeric and object series, as well as ``DataFrame`` column sets of mixed data types. The output will vary depending on what is provided. Refer to the notes below for more detail. ...
0.10版本加入了最新的cudf :: column和cudf :: table类,这些类大大提高了内存所有权控制的强健性,并为将来支持可变大小数据类型(包括字符串列、数组和结构)奠定了基础。由于已构建对整个libcudf API中的新类的支持,这项工作将在下一个版本周期中继续进行。此外,libcudf 0.10添加了许多新的API和算法,包括基于排序...
(group_cols) groups = groups[group_cols].values #groups用来存放分组的组类别 print(groups) #df_list是List类型,用来存放每个组的df df_list = [v_df[v_df[group_cols] == x] for x in groups] #合并df res = pd.concat(df_list) res.set_index(group_cols,inplace=True) return res my_...
唯一值unique # List unique values in a DataFrame column df['Column Name'].unique() 类型转换 ### Convert Series datatype to numeric (will error if column has non-numeric values) pd.to_numeric(df['Column Name']) ### Convert Series datatype to numeric, changing non-numeric values to ...
print('---') # np.nan :空值 # .mean()计算均值 # 只统计数字列 # 可以通过索引单独统计一列 m2= df.mean(axis=1) print(m2) print('---') # axis参数:默认为0,以列来计算,axis=1,以行来计算,这里就按照行来汇总了 m3= df.mean(skipna=False) print(...
#clear column 3 to 4 for i in df2["Item"].unique(): for x in range(3, len(df2.columns)): YCount =(df["Item" == i].df.iloc[:,x] == 'Y').sum() #count number of Y corresponding to the item NCount =(df["Item" == i].df.iloc[:,x] == 'N').sum() #count numb...
当然，notna()功能是相反的。它是检测现有（非缺失）值。8. unique()：获取一列的所有唯一值 对于分...
explode(column[, ignore_index])将列表的每个元素转换为行，复制索引值。ffill(*[, axis, inplace, ...