result = df.groupby(['G', 'User'])['C'].value_counts() yields G User 1 111 ar 1 112 es 2 2 112 es 1 113 es 1 3 113 es 2 4 114 es 1 dtype: int64 This counts each occurrence of ar and es. We really only want to count unique occurrences, so let's set each value ...
penguins_df["bill_length_mm"] = penguins_df["bill_length_mm"].apply(lambda x: x/10) 2. nunique() 此函数用于计算DataFrame列中唯一值的数量。 penguins_df["species"].nunique() 在此输出中,我们仅有3个独特物种。 3. sort_values() 此函数用于按升序或降序排序一个或多个列的DataFrame。 pengu...
Python pandas: How to group by and count unique values based on multiple columns? 3 Count unique values that are grouped by in Python 0 Count the number of unique values per group 5 Count of unique values per group as new column with pandas 1 Listing unique value counts per...
Series.unique() Return unique values of Series object. Returns: ndarray or ExtensionArray The unique values returned as a NumPy array. [33] pandas.DataFrame.isin DataFrame.isin(values) Whether each element in the DataFrame is contained in values. values: iterable, Series, DataFrame or dict Retur...
df.fillna(scala/{'col1':value1,'col2':value2,...},inplace=False) VI. 重复值处理 i) 判断Series的值、pandas对象的索引是否唯一 df['col1'].is_unique ii) 获取Series中的唯一值(返回数组) df['col1'].unique() iii)获取Series的重复部分和DataFrame的重复记录 ...
>>df['Age'].value_counts(bins=5)(16.336,32.252]346(32.252,48.168]188(0.339,16.336]100(48.168,64.084]69(64.084,80.0]11Name:Age,dtype:int64 count: Count non-NA cells for each column or row. 统计各列特征的非空值数量: >>df.count()PassengerId891Survived891Pclass891Name891Sex891Age714SibSp...
nunique count combine keys values set_axis isnull sparse first_valid_index combine_first ewm notnull empty mask truncate to_csv bool at clip radd to_markdown value_counts first isna between_time replace sample idxmin div iloc add_suffix pipe to_sql items max rsub flags sem to_string to_...
使用numpy/pandas函数的方法可能更有效，但这是我可以很快想到的，适用于通用的类别数量，而不必手动分离...
series.unique()->Array:返回Series对象中的唯一值数组,类似于sql中 distinct 列名,这样就不需要set(series.values.tolist())操作了。 `df["column_name"].value_counts()->Series:返回Series对象中每个取值的数量,类似于sql中group by(Series.unique())后再count() df["column_name"].isin(set or list-li...
基本的统计方法 Method Description count Number of non-NA values describe Compute set of summary statistics for Series or each DataFrame column min,max Comput