If you notice the above output, the actual column values that are part of the sum are not returned byDataFrame.sum()function, however, you can get all columns including the sum column by assigning theDataFrame.sum()to a DataFrame column. I would like to add a column'Sum'which is the s...
5155 method=method, 5156 copy=copy, 5157 level=level, 5158 fill_value=fill_value, 5159 limit=limit, 5160 tolerance=tolerance, 5161 ) File ~/work/pandas/pandas/pandas/core/generic.py:5610, in NDFrame.reindex(self, labels, index, columns, axis, method, copy, level, fill_value, limit...
(include=['int']).sum(1)df['total'] = df.loc[:,'Q1':'Q4'].apply(lambda x: sum(x), axis='columns') df.loc[:, 'Q10'] = '我是新来的' # 也可以 # 增加一列并赋值,不满足条件的为NaN df.loc[df.num >= 60, '成绩'] = '合格' df.loc[df.num < 60, '成绩'] = '不...
代码语言:javascript 复制 In [96]: dff = pd.DataFrame(np.arange(30, dtype=np.float64).reshape(10, 3), columns=list("ABC")) In [97]: dff.iloc[3:5, 0] = np.nan In [98]: dff.iloc[4:6, 1] = np.nan In [99]: dff.iloc[5:8, 2] = np.nan In [100]: dff Out[100]:...
根据什么分类columns:必选参数,设定列索引,用来显示字符型数据,和fill_value搭配使用。aggfunc:聚合函数, pivot_table后新dataframe的值都会通过aggfunc进行运算。默认numpy.mean求平均。fill_values:填充NA值(设定缺省值)。默认不填充,可以指定。margins:添加行列的总计,默认FALSE不显示。TRUE显示。dropna:如果整行都为NA...
df = pd.DataFrame(data, columns=columns) print(df) 1. 2. 3. 4. 5. 6. 7. 8. 输出结果同上。 从CSV文件创建: df = pd.read_csv('data.csv') print(df) 1. 2. 注意:这里假设data.csv文件与Python脚本在同一目录下,且文件内容格式正确。
pivot_table = data.pivot_table(values='price', index='category', columns='product', aggfunc=np.sum, fill_value=0) print(pivot_table) 这个示例代码中,我们首先使用 Pandas 的 read_csv 函数读取 CSV 文件中的数据,并使用 dropna 函数删除缺失值。然后,我们使用 drop_duplicates 函数删除重复行。接着...
pd.concat([df,df_new], axis='columns') 12.用多个函数聚合 orders = pd.read_csv('data/chipotle.tsv', sep='\t') orders.groupby('order_id').item_price.agg(['sum','count']).head() 13.分组聚合 import pandas as pd df = pd.DataFrame({'key1':['a', 'a', 'b', 'b', 'a'...
pd.pivot_table(df,index=["Manager","Status"],columns=["Product"],values=["Quantity","Price"], aggfunc={"Quantity":len,"Price":np.sum},fill_value=0) 此外,你也可以提供一系列的聚合函数,并将它们应用到“values”中的每个元素上。
Having specificdtypes In [12]:df2.dtypesOut[12]:A float64B datetime64[ns]C float32D int32E categoryF objectdtype: object If you’re using IPython, tab completion for column names (as well as public attributes) is automatically enabled. Here’s a subset of the attributes that will be ...