I have a data set that is spread across five columns. Sample of data:
Raw Data End Results
A B C D E A B C D E
1 2 2 1 6 1 2 2 1 6
0 3 3 0 6 0 3 3 0 6
1 2 2 1 6
0 3 3 0 6
1 2 2 1 6
0 3 3 0 6
1 2 2 1 6
0 3 3 0 6
1 2 2 1 6
0 3 3 0 6
1 2 2 1 6
0 3 3 0 6
1 2 2 1 6
0 3 3 0 6
The length of record varies from 10 to 40.
The data is to help me keep record of inventory and I wish to know which orders are popular.
Unfortunately I am still using Excel 2003.
Because I am not really sure what you have, this is deliberately simple:
In ColumnG Row1 put:
=A1&B1&C1&D1&E1
and copy down to suit. Select ColumnG and Paste Special, Values. Select ColumnG and sort. Insert in H1 and copy down to suit:
=COUNTIF(G$1:G1,G1)
1 should indicate the first ("unique") instance of each of the rows of Raw Data (and the other numbers the number of repetitions - up to 7 in your example, so one 'original' and six 'copies'.
Related
Starting Dataframe:
A B
0 1 1
1 1 2
2 2 3
3 3 4
4 3 5
5 1 6
6 1 7
7 1 8
8 2 9
Desired result - eg. Remove rows where column A has values that match the row above or below:
A B
0 1 1
2 2 3
3 3 4
5 1 6
8 2 9
You can use boolean indexing, the following condition will return true if value of A is NOT equal to value of A's next row
new_df = df[df['A'].ne(df['A'].shift())]
A B
0 1 1
2 2 3
3 3 4
5 1 6
8 2 9
In excel I have a dataset. This represents how much stock of 2 products is sold in the first, second, third, etc... month of the product being on the shelves (starts in A1):
Month 1 2 3 4 5 6 7 8 9 10 11 12
Product 1 3 5 2 1 6 1 2 4 7 2 1 5
Product 2 2 1 5 6 2 8 2 1 2 3 4 9
However, the first product sales do not always occur in month 1. They occur in month X. Is there a way (not VBA or copy and paste) of shifting the entries right by 'x' so they align with the month.
Example for data above
Product 1 starts in month 2
Product 2 starts in month 5
Month 1 2 3 4 5 6 7 8 9 10 11 12
Product 1 0 3 5 2 1 6 1 2 4 7 2 1 5
Product 2 0 0 0 0 2 1 5 6 2 8 2 1 2 3 4 9
*0 not required (great if possible), but more for illustration
Thanks
I have created a simple example that does the same job. The shown formula is copied over the shown cells in the row of new data. (The number '2' in the formula refers to the column number of the starting data cell which is column B, hence 2.)
I have a table like this
times v2
0 4 10
1 2 20
2 0 30/n30
3 1 40
4 0 9
What I want if change the values of v2 when times != 0, and the change consists in adding "\0" as many times as the times columns says.
times v2
0 4 10\n0\n0\n0\n0
1 2 20\n0\n0
2 0 30\n30
3 1 40\n0
4 0 9
You can do
df.v2+=df.times.map(lambda x : x*"\n0")
df
Out[325]:
times v2
0 4 10\n0\n0\n0\n0
1 2 20\n0\n0
2 0 30/n30
3 1 40\n0
4 0 9
Id
1
2
3
4
2
3
3
3
Questions
create one new column and that is newid
output should be like this.
id newid
1 1
2 1
3 1
4 1
2 0
3 0
3 0
3 0
Please suggest me how can I do it and which formula to be used in excel
1 2 2
4 5 4
3 3 3
0 1 0
1 2 2
4 4 3
4 5 4
4 5 4
3 4 4
3 4 4
4 4 4
3 4 3
I have above three columns in excel,how to find the number that appears more times, for example, first row is 2 (because it has two 2 and one 1)
Assuming your layout is such that the first column is A, second column is B, etc., then you could put the following in cell D1:
=IF(ISNUMBER(MODE(A1:C1)),MODE(A1:C1),0)
This also outputs 0 in case there is a tie. You can replace the 0 with whatever excel expression you want if you don't want ties to result in a 0.