# 定义一个函数,将值乘以2 def multiply_by_two(value): return value * 2 # 应用函数到列 'C' df['C'] = df['C'].apply(multiply_by_two) print("DataFrame after applying function: ", df) 对某一列的数据进行求和: 使用Pandas的sum方法,你可以轻松地对某一列的数据进行求和。 python # 对...
>>>s = pd.Series(['A','B','C'])>>>forindex, valueins.items():...print(f"Index :{index}, Value :{value}") Index :0, Value : A Index :1, Value : B Index :2, Value : C pandas.Series.keys 原文:pandas.pydata.org/docs/reference/api/pandas.Series.keys.html Series.keys()...
multiply函数需要一个权重列表或常数作为其必需参数。如果使用常数,则常数将乘以所有行或列(取决于axis的值)。如果使用列表,则列表中每个权重的位置对应于它所乘的行或列。 与sum和mean不同,multiply的默认轴是列轴。因此,如果要沿DataFrame的行应用权重,需要显式设置axis=0。 以下代码展示了multiply的示例用法。df...
['Quantity']) # multiply by Quantity .groupby(df['Symbol']) .transform('sum') # sum per group as new column) output: Position Symbol Action Quantity Price profit/loss0 Entry AA Sell 4 2.1 2.21 Partial AA Buy 2 1.5 2.22 Partial AA Buy 1 2.2 2.23 Partial AA Buy 1 1.0 2.24 Entry ...
DataFrame.multiply(other, axis='columns', level=None, fill_value=None) Parameters other:It can be a scalar, sequence, Series, or DataFrame. It can be a single or multiple element data structure, or list-like object. axis:It represents index or column axis, '0' for index and '1' for...
pandas 最常用的三种基本数据结构: 1、dataFrame: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html DataFrame相当于有表格(eg excel),有行表头和列表头 1.1初
value_counts() 24. CorrelationCorrelation means the relationship between two variables. The corr() method calculates the correlation coefficient between columns in a DataFrame.df.corr() 25. Cumulative FunctionsIn Pandas, cumulative functions are those functions that add up or multiply values ...
The same approach can be used to sum the values in a column based on multiple conditions. The following example sums the values in columnBwhere: The corresponding value in columnAis equal to5. And the corresponding value in columnCis equal to6. ...
asfreq slice_shift xs mad infer_objects rpow drop_duplicates mul cummax corr droplevel dtypes subtract rdiv filter multiply to_dict le dot aggregate pop rolling where interpolate head tail size iteritems rmul take iat to_hdf to_timestamp shift hist std sum at_time tz_localize axes swaplevel ...
Numpy基础 1、创建ndarray数组使用array函数,它接受一切序列型的对象,包括其他数组,然后产生一个新的Numpy数组。嵌套序列将会被转换成一个多维数组。...也可以在创建Series的时候为值直接创建索引。 b、通过字典的形式来创建Series。(3)获取Series中的值通过索引的