To count unique values in the Pandas DataFrame column use theSeries.unique()function along with the size attribute. Theseries.unique()function returns all unique values from a column by removing duplicate values and the size attribute returns a count of unique values in a column of DataFrame. S...
In [1]: import numba In [2]: def double_every_value_nonumba(x): return x * 2 In [3]: @numba.vectorize def double_every_value_withnumba(x): return x * 2 # 不带numba的自定义函数: 797 us In [4]: %timeit df["col1_doubled"] = df["a"].apply(double_every_value_nonumba) ...
unique() ## 11 种不同的折扣,从0折一直到10折 array([0.7, 0.1, 0.8, 0.4, 0.2, 0.3, 0.5, 1. , 0.6, 0.9, 0. ]) df['折扣'].value_counts() 0.2 43 0.4 42 0.3 41 0.7 38 0.6 34 0.1 33 0.8 33 0.5 30 0.9 26 1.0 21 0.0 19 Name: 折扣, dtype: int64 df['折扣'].value_...
Series(["S", "S", None, "M", "L", "S", None, "XL", "S", "M",]) # Get count of each value, it does not count missing values size.value_counts() 代码语言:python 代码运行次数:0 运行 AI代码解释 # pass dropna=False to get missing value count size.value_counts(dropna=False...
nunique:计算分组中唯一值的数量 cumsum、cummin、cummax...: 标记重复的行 drop_duplicates: 删除重复的行 str.strip: 去除字符串两端的空白字符 str.lower和 str.upper: 将字符串转换为小写或大写 str.replace...: 替换字符串中的特定字符 astype: 将一列的数据类型...
Pandas Count Unique Values in Column Pandas Count Distinct Values DataFrame Pandas DataFrame isna() function Pandas Get First Row Value of a Given Column Pandas Count The Frequency of a Value in Column References https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.count.html ...
nunique 函数是 pandas 中用于计算 DataFrame 或 Series 中唯一值的数量的函数。nunique 是 "number of unique" 的缩写，它返回一个标量值，表示唯一值的数量。以下是 nunique 函数的详细解释和用法：DataFrame/Series.nunique(axis=, dropna=True)主要参数：axis：默认为 0，用于指定计算唯一值数量的轴，0 表示...
Counting by unique pair of columnsFor this purpose, we will use groupby and apply the size() method on the group by an object.The groupby() is a simple but very useful concept in pandas. By using groupby, we can create grouping of certain values and perform some operations on those ...
(2) unique和nunique data['column'].nunique():显示有多少个唯一值 data['column'].unique():显示所有的唯一值 (3) count和value_counts data['column'].count():返回非缺失值元素个数 data['column'].value_counts():返回每个元素有多少个
# count of all unique values for the column course_difficultydf['course_difficulty'].value_counts() value_counts函数的基本用法 该value_counts函数以降序返回给定索引中所有唯一值的计数,不包含任何空值。我们可以很快地看到最大的课程具有初学者难度,其次是中级和混合,然后是高级。