How to Order a Data Frame by One Descending and One Ascending Column

How to order a data frame by one descending and one ascending column?

I used this code to produce your desired output. Is this what you were after?

rum <- read.table(textConnection("P1  P2  P3  T1  T2  T3  I1  I2
2   3   5   52  43  61  6   b
6   4   3   72  NA  59  1   a
1   5   6   55  48  60  6   f
2   4   4   65  64  58  2   b"), header = TRUE)
rum$I2 <- as.character(rum$I2)
rum[order(rum$I1, rev(rum$I2), decreasing = TRUE), ]

  P1 P2 P3 T1 T2 T3 I1 I2
1  2  3  5 52 43 61  6  b
3  1  5  6 55 48 60  6  f
4  2  4  4 65 64 58  2  b
2  6  4  3 72 NA 59  1  a

How to sort data by column in descending order in R

You need to use dataframe name as prefix

chickens[order(chickens$feathers),]  

To change the order, the function has decreasing argument

chickens[order(chickens$feathers, decreasing = TRUE),]  

How to sort ascending and descending depending on a value in another column in pandas?

If you can assume that your "price" column will always contain non-negative values, we could "cheat". Assign a negative value to the prices of buy or sell operations, sort, and then calculate the absolute value to go back to the original prices:

1. If type is "buy", the price remains positive (2 * 1 - 1 = 1). If type is "sell", the price will become negative (2 * 0 - 1 = -1).

   df["price"] = df["price"] * (2 * (df["type"] == "buy").astype(int) - 1)
   

2. Now sort values normally. I've included both "initiator_id" and "type" columns to match your expected output:

   df = df.sort_values(["initiator_id", "type", "price"])
   

3. Finally, calculate the absolute value of the "price" column to retrieve your original values:

   df["price"] = df["price"].abs()
   

Expected output of this operation on your sample input:

   initiator_id   price  type  bidnum
0             1  170.81  sell       0
2             2  169.19   buy       0
1             2  170.81  sell       0
4             3  169.19   buy       0
3             3  170.81  sell       0
5             3   70.81  sell       1
9             4   69.19   buy       1
7             4  169.19   buy       0
6             4  170.81  sell       0
8             4   70.81  sell       1

How to sort 2 columns in a Dataframe, one sorted in descending order and the other in alphabetical order corresponding to the 1st column

df = df.sort_values(['Rank', 'Name'],ascending = [False, True])

How to sort a Pandas DataFrame with multiple columns, some in ascending order and others descending order?

The DataFrame.sort_values method can handle this very easily. Just use the ascending argument and provide a list of boolean values.

import pandas as pd

my_df = pd.DataFrame({'col1':['a','a','a','a','b','b','b','b','c','c','c','c'],
                      'col2':[1,1,2,2,1,1,2,2,1,1,2,2],
                      'col3':[1,2,1,2,1,2,1,2,1,2,1,2]})

my_df = my_df.sort_values(by=['col1','col2','col3'], 
                          ascending=[False, False, True])

Note that the list provided in the ascending argument must have the same length as the one provided in the by argument.

R programming, how do I sort data frame by string column in descending order?

We can use decreasing = TRUE

temp[order(as.character(temp$y), decreasing = TRUE),]

R Sort one column ascending, all others descending (based on column order)

We can use arrange from dplyr

library(dplyr)
arrange(df, Size, desc(A), desc(B), desc(C))

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For more number of columns, arrange_ can be used

cols <-  paste0("desc(", names(df)[1:3], ")")
arrange_(df, .dots = c("Size", cols))

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