I am calculating the next excel table in VBA and leave the results as values because of a volume of data. But then I have to multiply these range by 1 or 0 depending on a column.
The problem is that I don't want to multiply by 0 becouse I gonna lose my data and have to recalculate it (I don't want it).
So, after my macro I get a next table, for example:
var.1 var.2 var.3
0 0 0
167 92 549
159 87 621
143 95 594
124 61 463
0 0 0
5 12 75
in a Range("A2:C9").
In a Range("A1:C1") i gonna have a 1 or 0 values that will be changing so i need my Range("A2:C9") to be like:
var.1 var.2 var.3
=0*A$1 =0*B$1 =0*C$1
=167*A$1 =92*B$1 =549*C$1
...
Is it possible to do with a macro? Thank's
And I would like to get
Okay so what I would do here is first copy the original data to another sheet or set of columns so that it is always preserved. Then use this formula:
=IF($A$1 = 0, 0,E3)
Instead of writing the cell E3 reference the data that you copied.
Related
After a simple merge of two dataframes the following X column becomes an object and an ".0" is being added at the end for no apparent reason. I tried replacing the nan values with an integer and then converting the whole column to an integer hoping for the .0 to be gone. The code runs but it doesn't really change the dtype of that column. Also, I tried removing the .0 with the rstrip command but then all it really does is it removes everything and even the values that are 249123.0 become NaN which doesn't make sense. I know that is a very basic issue but I am not sure what else could I try at this point.
Input:
Age ID
22 23105.0
34 214541.0
51 0
8 62341.0
Desired output:
Age ID
22 23105
34 214541
51 0
8 62341
Any ideas would be much appreciated.
One of the ways to get rid of the trailing .0 in an object column is to use pandas.DataFrame.replace :
df['ID'] = df['ID'].replace(r'\.0$', '', regex=True).astype(np.int64)
# Output :
print(df)
Age ID
0 22 23105
1 34 214541
2 51 0
3 8 62341
What I am trying to do if I have rows with the same prefix,fromMp, toMp
then I take the average of each TPCSpeed 1
for example I have
CF 116 117 54.8 56 50 50 50 50 50
CF 116 117 54.8 56 50 50 50 50 50
CF 116 117 54.8 56 50 50 50 50 50
so If the rows share the same from mp to mp prefix and suffix then I want to take the average TPC 1 of all the rows that share this for example for 116 117 I have TPC 1 (54.8+54.8+54.8)/(3)
I want to take the average of the tpc 1 column for all the rows which share the same info. If the rows do not share the same info I just want the tpc 1. Not sure how to do this maybe duplicates.
I am not sure how to to this in pandas
import pandas as pd
import numpy as np
result=pd.read_csv("result.csv")
a1=result.columns.get_loc("TPCSpeed1")
a2=result.columns.get_loc("TPCSpeed2")
a3=result.columns.get_loc("TPCSpeed3")
a4=result.columns.get_loc("TPCSpeed4")
a5=result.columns.get_loc("TPCSpeed5")
a6=result.columns.get_loc("TPCSpeed6")
a7=result.columns.get_loc("TPCSpeed7")
pre=result.columns.get_loc("Prefix")
suf=result.columns.get_loc("Suffix")
FromMp=result.columns.get_loc("FromMP")
ToMp=result.columns.get_loc("ToMP")
w1=[]
w2=[]
w3=[]
w4=[]
w5=[]
w6=[]
w7=[]
prefix=[]
suffix=[]
begin=[]
end=[]
for index,row in result.iterrows():
print(index)
c1=row[pre]
c2=row[suf]
c3=row[FromMp]
c4=row[ToMp]
prefix.append(c1)
suffix.append(c2)
begin.append(c3)
end.append(c4)
b1=row[a1]
w1.append(b1)
b2=row[a2]
w2.append(b2)
b3=row[a3]
w3.append(b3)
b4=row[a4]
w4.append(b4)
b5=row[a5]
w5.append(b5)
b6=row[a6]
w6.append(b6)
b7=row[a7]
w7.append(b7)
This is a good use for groupby().agg().
At it's simplest, you can try:
result.groupbby(['Prefix', 'FromMP', 'ToMP', 'Suffix').agg(np.mean)
This will collapse all rows that have the same values in all four named columns, and then replace them with a single row with the mean values in each of the other columns. You can use reset_index() to get back to the original dataframe.
The agg (aka aggregate) function is fairly flexible. You can treat columns differently. It doesn't have to be the average for everything.
https://pandas.pydata.org/docs/reference/api/pandas.core.groupby.DataFrameGroupBy.aggregate.html
I have a very large dataframe (original_df) with columns of codes
14 15
21 22
18 16
And a second dataframe (crosswalk) which maps 'old_codes' to 'new_codes'
14 104
15 105
16 106
18 108
21 201
22 202
Of course, the resultant df (resultant_df) that I would like would have values:
104 105
201 202
108 106
I am aware of two ways to accomplish this. First, I could iterate through each code in original_df, find the code in crosswalk, then rewrite the corresponding cell in original_df with the translated code from crosswalk. The faster and more natural option would be to leftjoin() each column of original_df on 'old_codes'. Unfortunately, it seems I have to do this separately for each column, and then delete each column after its conversion column has been created -- this feels unnecessarily complicated. Is there a simpler way to convert all of original_df at once using the crosswalk?
You can do the following (I am using column numbers as you have not provided column names):
d = Dict(crosswalk[!, 1] .=> crosswalk[!, 2])
resultant_df = select(original_df, [i => ByRow(x -> d[x]) for i in 1:ncol(original_df)], renamecols=false)
I'm trying to automate billing for my boss. I have to choose the highest quantity for an invoice date and client, then print that quantity in a separate column and a 0 (or blank) for the second row associated with that client. I'm trying to recreate this example:
Billing Snippet
I'm having trouble using Pandas to do this. I used a pivot table to get the max quantity for each client, then merged that data with the original to get a "max" column. That looks like this:
Dataframe snippet
My plan is to use indexes to essentially say "if the Qty is not equal to Max, then change the value to 0"
Here's my code, but I get the error "A value is trying to be set on a copy of a slice from a DataFrame" :
ad2[ad2['Qty'] != ad2['max']]['Qtrly Billing Count']=0
Any advice on how to tackle this?
Update: Tried turning off the setting that gives me the index error, but the column I want to update isn't changing. Help!
Recreating you df:
ad2 = pd.DataFrame({'Qty':[33, 47],'max':[47,47], 'Qtrly':[47,47] })
Qtrly Qty max
0 47 33 47
1 47 47 47
using loc:
ad2.loc[ad2['Qty'] != ad2['max'], 'Qtrly']=0
result:
Qtrly Qty max
0 0 33 47
1 47 47 47
I am working on vba code where I have data (for Slope Inclinometers) at various depths like so:
Depth A0 A180 Checksum B0 B180 Checksum
4.5 (-1256) 1258 2 (-394) 378 (-16)
4.5 (-1250) 1257 7 (-396) 376 (-20)
4.5 (-1257) 1257 0 (-400) 374 (-26)
Depth A0 A180 Checksum B0 B180 Checksum
5 (-1214) 1214 0 (-472) 459 (-13)
5 (-1215) 1212 -3 (-472) 455 (-17)
5 (-1216) 1211 -5 (-473) 455 (-18)
UNKNOWN AMOUNT OF DATA WILL BE PRESENT (depends how much the user transfers to this sheet)
Now I need to be able to calculate the A Axis Displacement, the B Axis Displacement, and the resultant which have formulas as followed:
A Axis Displacement = [((A0-A180)/2)-((A0*-A180*)/2))]*(constant/constant)
Where * is the initial readings which is always the first row of data at that specified depth.
B Axis Displacement = [((A0-A180)/2)-((A0*-A180*)/2))]*(constant/constant)
Where * is the initial readings which is always the first row of data at that specified depth.
Resultant = SQRT[(A Axis Displacement)^2 + (B Axis Displacement)^2]
I'm struggling to find examples of how I can implement this using vba as there will be various depths present (unknown amount) on the same sheet where the formula will need to start over at each new depth present.
Any helps/tips would be greatly appreciated!
how I can implement this using vba as there will be various depths present...
You still can do it purely with formulas and easy auto-fill, because the formula can find the the first occurrence of the current depth and perform all the necessary calculations, leaving blank at header rows or blank rows. For instance, you can enter these formulas at row 2 and fill down all the rows.
H2 (A Axis Displacement):
=IF(ISNUMBER($A2),0.5*(B2-C2-VLOOKUP($A2,$A:$F,2,0)+VLOOKUP($A2,$A:$F,3,0)), "")
I2 (B Axis Displacement):
=IF(ISNUMBER($A2),0.5*(E2-F2-VLOOKUP($A2,$A:$F,5,0)+VLOOKUP($A2,$A:$F,6,0)), "")
J2 (Resultant):
=IF(ISNUMBER($A2),SQRT(SUMSQ(H2,I2)),"")
p.s. in the displacements formulas I omitted the (constant/constant) factor as it is irrelevant to the answer, you can easily multiply the 0.5 factor by anything you need.