[英]Pandas Pivot Table counting based on condition and sum columns
I have DateFrame as shown below.我有如下所示的 DateFrame。 I need to add a few columns to dft (pivot output).
我需要向 dft(枢轴输出)添加几列。 First one to calculate sum of products sold daily, it's like margine but only for sum column not len.
第一个计算每天销售的产品总和,这就像marine,但仅适用于总和列而不是len。 I tried dft['Fruit Total']=df.iloc[:,0:3].sum(axis=1) but it didn't work.
我试过 dft['Fruit Total']=df.iloc[:,0:3].sum(axis=1) 但没有用。 also I want to add column counting values > than 2 for each row in column sum.
我还想为列总和中的每一行添加大于 2 的列计数值。 like in the picture
就像在图片中
df = pd.DataFrame({
'date': ["22.10.2021", "22.10.2021", "22.10.2021", "23.10.2021", "23.10.2021", "25.10.2021", "22.10.2021", "23.10.2021", "22.10.2021", "25.10.2021"],
'Product': ["apple", "apple", "orange", "orange", "apple","apple", "apple", "orange", "orange", "orange"],
'sold_kg': [2, 3, 1, 6, 2,2, 3, 1, 6, 2,]})
df['day']=pd.to_datetime(df['date']).dt.day
dft=df.pivot_table(values='sold_kg', columns ='day', index='Product', aggfunc=[np.sum,len])
dft
Use:利用:
dft=df.pivot_table(values='sold_kg',columns='day', index='Product', aggfunc=['sum','size'])
First flatten MultiIndex in columns
with mapping:首先在具有映射
MultiIndex in columns
:
dft.columns = dft.columns.map(lambda x: f'{x[0]}_{x[1]}')
Then select columns by DataFrame.filter
and sum
, for count values greater or equal use DataFrame.ge
and count True
s by sum
:然后通过
DataFrame.filter
和sum
选择列,对于大于或等于的计数值,使用DataFrame.ge
并通过sum
计数True
s:
dft['Fruit Total'] = dft.filter(like='sum').sum(axis=1)
dft['Count >= 2'] = dft.filter(like='size').ge(2).sum(axis=1)
print (dft)
sum_22 sum_23 sum_25 size_22 size_23 size_25 Fruit Total \
Product
apple 8 2 2 3 1 1 12
orange 7 7 2 2 2 1 16
Count >= 2
Product
apple 1
orange 2
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