Reputation: 254
working code in R
library(dplyr)
tmp <- test %>%
group_by(InvoiceDocNumber) %>%
summarise(invoiceprob=max(itemprob)) %>%
mutate(invoicerank=rank(desc(invoiceprob)))
But I want to rewrite the code in python. I wrote the below code but it's throwing me the error. I am using the similar version of dplyr which is available in python.
from dfply import *
tmp = (test >>
group_by(test.InvoiceDocNumber) >>
summarize(invoiceprob=max(test.itemprob)) >>
mutate(invoicerank=rankdata(test.invoiceprob)))
AttributeError: 'DataFrame' object has no attribute 'invoiceprob'
Can anyone help me ?
Upvotes: 4
Views: 13653
Reputation: 3825
You would like to use: datar
(I am the author)
from datar.all import *
tmp = test >> \
group_by(f.InvoiceDocNumber) >> \
summarise(invoiceprob=max(f.itemprob)) >> \
mutate(invoicerank=rank(desc(f.invoiceprob)))
Upvotes: 0
Reputation: 21264
You can use assign
to get it all in one chain:
(
test.groupby("InvoiceDocNumber", as_index=False)
.itemprob.max()
.rename(columns={"itemprob":"invoiceprob"})
.assign(invoicerank = lambda x: x.invoiceprob.rank(ascending=False))
)
Output:
InvoiceDocNumber invoiceprob invoicerank
0 0 0.924193 5.0
1 1 0.974173 4.0
2 2 0.978962 3.0
3 3 0.992663 2.0
4 4 0.994243 1.0
Data:
import numpy as np
import pandas as pd
n = 100
test = pd.DataFrame({"InvoiceDocNumber": np.random.choice(np.arange(5), size=n),
"itemprob": np.random.uniform(size=n)})
Upvotes: 3
Reputation: 254
I got the answer
ddd = test.groupby('InvoiceDocNumber', as_index=False).agg({"itemprob": "max"})
ddd= ddd.rename(columns={'itemprob': 'invoiceprob'})
ddd['invoicerank'] =ddd['invoiceprob'].rank(ascending=0)
Upvotes: 0