unique()) ['东莞' '深圳' '广州' '北京' '上海' '南京'] 六、查看数据表数值 import pandas as pd df = pd.DataFrame(pd.read_excel('test.xlsx', engine='openpyxl')) print(df.values) [[1001 Timestamp('2024-01-02 00:00:00') '东莞' '100-A' 23 1200.0] [1002 Timestamp('2024-01...
In the above example, thenunique()function returns a pandas Series with counts of distinct values in each column. Note that, for theDepartmentcolumn we only have two distinct values as thenunique()function, by default, ignores all NaN values. 2. Count of unique values in each row You can ...
(self) 1489 ref = self._get_cacher() 1490 if ref is not None and ref._is_mixed_type: 1491 self._check_setitem_copy(t="referent", force=True) 1492 return True -> 1493 return super()._check_is_chained_assignment_possible() ~/work/pandas/pandas/pandas/core/generic.py in ?(self) ...
大部分 Pandas 都严重依赖ndarray。 在索引,列和数据之下是 NumPyndarrays。 可以将它们视为构建许多其他对象的 Pandas 的基本对象。 要看到这一点,我们可以查看index和columns的值: >>> index.valuesarray([ 0, 1, 2, ..., 4913, 4914, 4915])>>> columns.valuesarray(['color', 'director_name', 'n...
But what if you don’t have a single column that can do this? For example, you have the columns “name”, “age”, “address”, and “marks” in a DataFrame. Any of the above columns may not have unique values for all the different rows and are unfit as indexes. However, the ...
py in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs) 3089 3090 kwargs['mgr'] = self -> 3091 applied = getattr(b, f)(**kwargs) 3092 result_blocks = _extend_blocks(applied, result_blocks) 3093 /Users/Ted/anaconda/lib/python3.6/site-packages/pandas/core/...
Pandas version checks I have checked that this issue has not already been reported. I have confirmed this bug exists on the latest version of pandas. I have confirmed this bug exists on the main branch of pandas. Reproducible Example Exa...
select: this creates a dropdown populated with the unique values of "column" (an asynchronous dropdown if the column has a large amount of unique values) multiselect: same as "select" but it will allow you to choose multiple values (handy if you want to perform an isin operation in your...
DataFrame.pivot_table(self, values=None, index=None, columns=None, aggfunc='mean', fill_value=None, margins=False, dropna=True, margins_name='All', observed=False)pivot_tabel对数据格式要求不高,而且支持aggfunc/fillvalue等参数,所以应用更加广泛。 pivot_table函数的参数有values(单元格值)、index(索...
2.ValueError: cannot handle a non-unique multi-index! 在对多级索引进行操作时,可能会遇到此错误。 原因:多级索引中存在重复值。 解决方法:确保索引唯一性,或使用reset_index()方法重置索引。 # 检查是否有重复索引ifdf.index.duplicated().any():