是的,'DataFrame' 对象没有 'unique' 属性,您可能想使用的是 'nunique' 方法。 在Pandas 中,DataFrame 对象确实没有 unique 属性,但有一个 nunique 方法,用于计算每列或每行中唯一值的数量。如果您想获取 DataFrame 中某一列的唯一值,可以使用 Series.unique() 方法,因为 DataFrame 的每一列本质上都是一个...
slice data frames and assign the values to a new data frame using row numbers and column names. The code assigns the first three rows and all columns in between to the columns named Artist and Released. Creating a new dataframe with iloc slicing In this example, we assign the first two...
unique_values = s_df['x'].value_counts() print(unique_values) Output: 2 2 7 1 1 1 Name: x, dtype: int64 Conclusion In conclusion, the error'dataframe' object has no attribute 'unique'is quick to solve by replacing theunique()method with an appropriate one. ...
# Add the prefix 'UID_' to the ID values df['UID'] = 'UID_' + df['UID'].astype(str).apply(lambda x: x.zfill(6)) print(df) The reset_index() function in pandas is used to reset the index of a DataFrame. By default, it resets the index to the default integer index and ...
What happened + What you expected to happen I wanted to get the unique values in a given column of my dataset, but some of the values are null for unavoidable reasons. Calling Dataset.unique(colname) on such data raises a TypeError, with...
Generate unique increasing numeric values Use Apache Spark functions to generate unique and increasing numbers in a column in a table in a file or DataFrame. This article shows you how to use Apache Spark functions to generate unique increasing numeric values in a column....
get_level_values(0).freq) None >>> print(multi_index.get_level_values(“Dates”).freq) None Issue Description For a DatetimeIndex contained in a MultiIndex get_level_values() returns a DatetimeIndex without frequency, even if the frequency is set and available in the internal structure (i....
print(b.sort_values(["avg", 'city'], ascending=False)) print("15,---") # 将平均值排名默认 b["rank"] = b.avg.rank(ascending=False, method="first") # 将平均值排名最小 b["rank"] = b.avg.rank(ascending=False, method="min") # 将平均...
DataFrame.sort_values(self, by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last')#axis这个参数的默认值为0,匹配的是index,跨行进行排序,当axis=1时,匹配的是columns,跨列进行排序#by这个参数要求传入一个字符或者是一个字符列表,用来指定按照axis的中的哪个元素来进行排序#...
("Original DataFrame:")print(df)new_df=df[['id','type','book']].drop_duplicates()\.groupby(['id','type'])['book']\.apply(list)\.reset_index()new_df['book']=new_df.apply(lambdax:(','.join([str(s)forsinx['book']])),axis=1)print("\nList all unique values in a group...