Creating multiple named dataframes by a for loop - python-3.x
I have a database that contains 60,000+ rows of college football recruit data. From there, I want to create seperate dataframes where each one contains just one value. This is what a sample of the dataframe looks like:
,Primary Rank,Other Rank,Name,Link,Highschool,Position,Height,weight,Rating,National Rank,Position Rank,State Rank,Team,Class
0,1,,D.J. Williams,https://247sports.com/Player/DJ-Williams-49931,"De La Salle (Concord, CA)",ILB,6-2,235,0.9998,1,1,1,Miami,2000
1,2,,Brock Berlin,https://247sports.com/Player/Brock-Berlin-49926,"Evangel Christian Academy (Shreveport, LA)",PRO,6-2,190,0.9998,2,1,1,Florida,2000
2,3,,Charles Rogers,https://247sports.com/Player/Charles-Rogers-49984,"Saginaw (Saginaw, MI)",WR,6-4,195,0.9988,3,1,1,Michigan State,2000
3,4,,Travis Johnson,https://247sports.com/Player/Travis-Johnson-50043,"Notre Dame (Sherman Oaks, CA)",SDE,6-4,265,0.9982,4,1,2,Florida State,2000
4,5,,Marcus Houston,https://247sports.com/Player/Marcus-Houston-50139,"Thomas Jefferson (Denver, CO)",RB,6-0,208,0.9980,5,1,1,Colorado,2000
5,6,,Kwame Harris,https://247sports.com/Player/Kwame-Harris-49999,"Newark (Newark, DE)",OT,6-7,320,0.9978,6,1,1,Stanford,2000
6,7,,B.J. Johnson,https://247sports.com/Player/BJ-Johnson-50154,"South Grand Prairie (Grand Prairie, TX)",WR,6-1,190,0.9976,7,2,1,Texas,2000
7,8,,Bryant McFadden,https://247sports.com/Player/Bryant-McFadden-50094,"McArthur (Hollywood, FL)",CB,6-1,182,0.9968,8,1,1,Florida State,2000
8,9,,Sam Maldonado,https://247sports.com/Player/Sam-Maldonado-50071,"Harrison (Harrison, NY)",RB,6-2,215,0.9964,9,2,1,Ohio State,2000
9,10,,Mike Munoz,https://247sports.com/Player/Mike-Munoz-50150,"Archbishop Moeller (Cincinnati, OH)",OT,6-7,290,0.9960,10,2,1,Tennessee,2000
10,11,,Willis McGahee,https://247sports.com/Player/Willis-McGahee-50179,"Miami Central (Miami, FL)",RB,6-1,215,0.9948,11,3,2,Miami,2000
11,12,,Antonio Hall,https://247sports.com/Player/Antonio-Hall-50175,"McKinley (Canton, OH)",OT,6-5,295,0.9946,12,3,2,Kentucky,2000
12,13,,Darrell Lee,https://247sports.com/Player/Darrell-Lee-50580,"Kirkwood (Saint Louis, MO)",WDE,6-5,230,0.9940,13,1,1,Florida,2000
13,14,,O.J. Owens,https://247sports.com/Player/OJ-Owens-50176,"North Stanly (New London, NC)",S,6-1,195,0.9932,14,1,1,Tennessee,2000
14,15,,Jeff Smoker,https://247sports.com/Player/Jeff-Smoker-50582,"Manheim Central (Manheim, PA)",PRO,6-3,190,0.9922,15,2,1,Michigan State,2000
15,16,,Marco Cooper,https://247sports.com/Player/Marco-Cooper-50171,"Cass Technical (Detroit, MI)",OLB,6-2,235,0.9918,16,1,2,Ohio State,2000
16,17,,Chance Mock,https://247sports.com/Player/Chance-Mock-50163,"The Woodlands (The Woodlands, TX)",PRO,6-2,190,0.9918,17,3,2,Texas,2000
17,18,,Roy Williams,https://247sports.com/Player/Roy-Williams-55566,"Permian (Odessa, TX)",WR,6-4,202,0.9916,18,3,3,Texas,2000
18,19,,Matt Grootegoed,https://247sports.com/Player/Matt-Grootegoed-50591,"Mater Dei (Santa Ana, CA)",OLB,5-11,205,0.9914,19,2,3,USC,2000
19,20,,Yohance Buchanan,https://247sports.com/Player/Yohance-Buchanan-50182,"Douglass (Atlanta, GA)",S,6-1,210,0.9912,20,2,1,Florida State,2000
20,21,,Mac Tyler,https://247sports.com/Player/Mac-Tyler-50572,"Jess Lanier (Hueytown, AL)",DT,6-6,320,0.9912,21,1,1,Alabama,2000
21,22,,Jason Respert,https://247sports.com/Player/Jason-Respert-55623,"Northside (Warner Robins, GA)",OC,6-3,300,0.9902,22,1,2,Tennessee,2000
22,23,,Casey Clausen,https://247sports.com/Player/Casey-Clausen-50183,"Bishop Alemany (Mission Hills, CA)",PRO,6-4,215,0.9896,23,4,4,Tennessee,2000
23,24,,Albert Means,https://247sports.com/Player/Albert-Means-55968,"Trezevant (Memphis, TN)",SDE,6-6,310,0.9890,24,2,1,Alabama,2000
24,25,,Albert Hollis,https://247sports.com/Player/Albert-Hollis-55958,"Christian Brothers (Sacramento, CA)",RB,6-0,190,0.9890,25,4,5,Georgia,2000
25,26,,Eric Moore,https://247sports.com/Player/Eric-Moore-55973,"Pahokee (Pahokee, FL)",OLB,6-4,226,0.9884,26,3,3,Florida State,2000
26,27,,Willie Dixon,https://247sports.com/Player/Willie-Dixon-55626,"Stockton Christian School (Stockton, CA)",WR,5-11,182,0.9884,27,4,6,Miami,2000
27,28,,Cory Bailey,https://247sports.com/Player/Cory-Bailey-50586,"American (Hialeah, FL)",S,5-10,175,0.9880,28,3,4,Florida,2000
28,29,,Sean Young,https://247sports.com/Player/Sean-Young-55972,"Northwest Whitfield County (Tunnel Hill, GA)",OG,6-6,293,0.9878,29,1,3,Tennessee,2000
29,30,,Johnnie Morant,https://247sports.com/Player/Johnnie-Morant-60412,"Parsippany Hills (Morris Plains, NJ)",WR,6-5,225,0.9871,30,5,1,Syracuse,2000
30,31,,Wes Sims,https://247sports.com/Player/Wes-Sims-60243,"Weatherford (Weatherford, OK)",OG,6-5,310,0.9869,31,2,1,Oklahoma,2000
31,33,,Jason Campbell,https://247sports.com/Player/Jason-Campbell-55976,"Taylorsville (Taylorsville, MS)",PRO,6-5,190,0.9853,33,5,1,Auburn,2000
32,34,,Antwan Odom,https://247sports.com/Player/Antwan-Odom-50168,"Alma Bryant (Irvington, AL)",SDE,6-7,260,0.9851,34,3,2,Alabama,2000
33,35,,Sloan Thomas,https://247sports.com/Player/Sloan-Thomas-55630,"Klein (Spring, TX)",WR,6-2,188,0.9847,35,6,5,Texas,2000
34,36,,Raymond Mann,https://247sports.com/Player/Raymond-Mann-60804,"Hampton (Hampton, VA)",ILB,6-1,233,0.9847,36,2,1,Virginia,2000
35,37,,Alphonso Townsend,https://247sports.com/Player/Alphonso-Townsend-55975,"Lima Central Catholic (Lima, OH)",DT,6-6,280,0.9847,37,2,3,Ohio State,2000
36,38,,Greg Jones,https://247sports.com/Player/Greg-Jones-50158,"Battery Creek (Beaufort, SC)",RB,6-2,245,0.9837,38,6,1,Florida State,2000
37,39,,Paul Mociler,https://247sports.com/Player/Paul-Mociler-60319,"St. John Bosco (Bellflower, CA)",OG,6-5,300,0.9833,39,3,7,UCLA,2000
38,40,,Chris Septak,https://247sports.com/Player/Chris-Septak-57555,"Millard West (Omaha, NE)",TE,6-3,245,0.9833,40,1,1,Nebraska,2000
39,41,,Eric Knott,https://247sports.com/Player/Eric-Knott-60823,"Henry Ford II (Sterling Heights, MI)",TE,6-4,235,0.9831,41,2,3,Michigan State,2000
40,42,,Harold James,https://247sports.com/Player/Harold-James-57524,"Osceola (Osceola, AR)",S,6-1,220,0.9827,42,4,1,Alabama,2000
For example, if I don't use a for loop, this line of code is what I use if I just want to create one dataframe:
recruits2022 = recruits_final[recruits_final['Class'] == 2022]
However, I want to have a named dataframe for each recruiting class.
In other words, recruits2000 would be a dataframe for all rows that have a class value equal to 2000, recruits2001 would be a dataframe for all rows that have a class value to 2001, and so forth.
This is what I tried recently, but have no luck saving the dataframe outside of the for loop.
databases = ['recruits2000', 'recruits2001', 'recruits2002', 'recruits2003', 'recruits2004',
'recruits2005', 'recruits2006', 'recruits2007', 'recruits2008', 'recruits2009',
'recruits2010', 'recruits2011', 'recruits2012', 'recruits2013', 'recruits2014',
'recruits2015', 'recruits2016', 'recruits2017', 'recruits2018', 'recruits2019',
'recruits2020', 'recruits2021', 'recruits2022', 'recruits2023']
for i in range(len(databases)):
year = pd.to_numeric(databases[i][-4:], errors = 'coerce')
db = recruits_final[recruits_final['Class'] == year]
db.name = databases[i]
print(db)
print(db.name)
print(year)
recruits2023
I would get this error instead of what I wanted
NameError Traceback (most recent call last)
<ipython-input-49-7cb5d12ab92f> in <module>()
29
30 # print(db.name)
---> 31 recruits2023
32
33
NameError: name 'recruits2023' is not defined
Is there something that I am missing to get this for loop to work? Any assistance is truly appreciated. Thanks in advance.
List use a dictionary of dataframes using groupby:
dict_dfs = dict(tuple(df.groupby('Class')))
Access you individual dataframes using
dict_dfs[2022]
You override variable db at each iteration and recruits2023 is not a variable so you can't use it like that:
You can use a dict to store your data:
recruits = {}
for year in recruits_final['Class'].unique():
recruits[year] = recruits_final[recruits_final['Class'] == year]
>>> recruits[2000]
Primary Rank Other Rank Name Link ... Position Rank State Rank Team Class
0 1 NaN D.J. Williams https://247sports.com/Player/DJ-Williams-49931 ... 1 1 Miami 2000
1 2 NaN Brock Berlin https://247sports.com/Player/Brock-Berlin-49926 ... 1 1 Florida 2000
2 3 NaN Charles Rogers https://247sports.com/Player/Charles-Rogers-49984 ... 1 1 Michigan State 2000
3 4 NaN Travis Johnson https://247sports.com/Player/Travis-Johnson-50043 ... 1 2 Florida State 2000
...
38 40 NaN Chris Septak https://247sports.com/Player/Chris-Septak-57555 ... 1 1 Nebraska 2000
39 41 NaN Eric Knott https://247sports.com/Player/Eric-Knott-60823 ... 2 3 Michigan State 2000
40 42 NaN Harold James https://247sports.com/Player/Harold-James-57524 ... 4 1 Alabama 2000
>>> recruits.keys()
dict_keys([2000])
Related
Create New DataFrame Columns Based on Year
I have a pandas DataFrame that contains NFL Quarterback Data from the 2015-2016 to the 2019-2020 Seasons. The DataFrame looks like this Player Season End Year YPG TD Tom Brady 2019 322.6 25 Tom Brady 2018 308.1 26 Tom Brady 2017 295.7 24 Tom Brady 2016 308.7 28 Aaron Rodgers 2019 360.4 30 Aaron Rodgers 2018 358.8 33 Aaron Rodgers 2017 357.9 35 Aaron Rodgers 2016 355.2 32 I want to be able to create new columns that contains the years' data I select and the last three years' data. For example if the year I select is 2019 the resulting DataFrame would be(SY stands for selected year: Player Season End Year YPG SY YPG SY-1 YPG SY-2 YPG SY-3 TD Tom Brady 2019 322.6 308.1 295.7 308.7 25 Aaron Rodgers 2019 360.4 358.8 357.9 355.2 30 This is how I am attempting to do it: NFL_Data.loc[NFL_Data['Season End Year'] == (NFL_Data['SY']), 'YPG SY'] = NFL_Data['YPG'] NFL_Data.loc[NFL_Data['Season End Year'] == (NFL_Data['SY']-1), 'YPG SY-1'] = NFL_Data['YPG'] NFL_Data.loc[NFL_Data['Season End Year'] == (NFL_Data['SY']-2), 'YPG SY-2'] = NFL_Data['YPG'] NFL_Data.loc[NFL_Data['Season End Year'] == (NFL_Data['SY']-3), 'YPG SY-3'] = NFL_Data['YPG'] However, when I run the code above, it doesn't fill out the columns appropriately. Most of the rows are 0. Am I approaching the problem the right way or is there a better way to attack it? (Edited to include TD Column)
First step is to pivot your data frame. pivoted = df.pivot_table(index='Player', columns='Season End Year', values='YPG') Which yields Season End Year 2016 2017 2018 2019 Player Aaron Rodgers 355.2 357.9 358.8 360.4 Tom Brady 308.7 295.7 308.1 322.6 Then, you may select: pivoted.loc[:, range(year, year-3, -1)] 2019 2018 2017 Player Aaron Rodgers 360.4 358.8 357.9 Tom Brady 322.6 308.1 295.7 Or alternatively as suggested by Quang: pivoted.loc[:, year:year-3:-1]
Copy row of data from one pandas dataframe to another
A pandas newbie here. I imported an excel data into pandas, I want to copy subset of data of a specific row (placeholder) from one dataframe (Error_data1) to another dataframe (Error_data2) where the 'placeholder' exists. Here is the first 4 rows of Error_data1 (it has 150 rows) index student Error1 Error2 Error3 Error4 Error5 0 Henry 2.5647 -0.2145 1.3524 2.0124 6.2013 1 John -0.0124 1.0365 3.2145 4.0211 -5.0124 2 Terry 1.1120 2.2154 -6.2013 1.2032 2.3321 3 Gerald 9.2105 1.0212 3.2548 3.6478 4.1020 Here is the first 5 rows of Error_data2 (it has 358 rows) index Day Time student Error1 Error2 Error3 Error4 Error5 0 Mon 01:00 Terry 1 Tue 05:15 John 2 Wed 05:25 john 3 Wed 12:15 Gerald 4 Thur 11:00 Henry Here is the code i tried for i in range(len(Error_data1)): if Error_data1['Student'][i] == Error_data2['Student'][i]: a = Error_data1.iloc[i,1:6] Error_data2.iloc[i,4:9] = a I expect Error_data2 to look like this: index Day Time student Error1 Error2 Error3 Error4 Error5 0 Mon 01:00 Terry 1.1120 2.2154 -6.2013 1.2032 2.3321 1 Tue 05:15 John -0.0124 1.0365 3.2145 4.0211 -5.0124 2 Wed 05:25 john -0.0124 1.0365 3.2145 4.0211 -5.0124 3 Wed 12:15 Gerald 9.2105 1.0212 3.2548 3.6478 4.1020 4 Thur 11:00 Henry 2.5647 -0.2145 1.3524 2.0124 6.2013
You can try merging the two dataframes on student names. combined = Error_data1.merge(Error_data2, on='student', how='left').fillna(0)
Bokeh Dodge Chart using Different Pandas DataFrame
everyone! So I have 2 dataframes extracted from Pro-Football-Reference as a csv and run through Pandas with the aid of StringIO.
I'm pasting only the header and a row of the info right below:
data_1999 = StringIO("""Tm,W,L,W-L%,PF,PA,PD,MoV,SoS,SRS,OSRS,DSRS Indianapolis Colts,13,3,.813,423,333,90,5.6,0.5,6.1,6.6,-0.5""")
data = StringIO("""Tm,W,L,T,WL%,PF,PA,PD,MoV,SoS,SRS,OSRS,DSRS Indianapolis Colts,10,6,0,.625,433,344,89,5.6,-2.2,3.4,3.9,-0.6""")
And then interpreted normally using pandas.read_csv, creating 2 different dataframes called df_nfl_1999 and df_nfl respectively.
So I was trying to use Bokeh and do something like here, except instead of 'apples' and 'pears' would be the name of the teams being the main grouping. I tried to emulate it by using only Pandas Dataframe info:
p9=figure(title='Comparison 1999 x 2018',background_fill_color='#efefef',x_range=df_nfl_1999['Tm'])
p9.xaxis.axis_label = 'Team'
p9.yaxis.axis_label = 'Variable'
p9.vbar(x=dodge(df_nfl_1999['Tm'],0.0,range=p9.x_range),top=df_nfl_1999['PF'],legend='PF in 1999', width=0.3)
p9.vbar(x=dodge(df_nfl_1999['Tm'],0.25,range=p9.x_range),top=df_nfl['PF'],legend='PF in 2018', width=0.3, color='#A6CEE3')
show(p9)
And the error I got was:
ValueError: expected an element of either String, Dict(Enum('expr',
'field', 'value', 'transform'), Either(String, Instance(Transform),
Instance(Expression), Float)) or Float, got {'field': 0
Washington Redskins
My initial idea was to group by Team Name (df_nfl['Tm']), analyzing the points in favor in each year (so df_nfl['PF'] for 2018 and df_nfl_1999['PF'] for 1999). A simple offset of the columns could resolve, but I can't seem to find a way to do this, other than the dodge chart, and it's not really working (I'm a newbie).
By the way, the error reference is appointed at happening on the:
p9.vbar(x=dodge(df_nfl_1999['Tm'],0.0,range=p9.x_range),top=df_nfl_1999['PF'],legend='PF in 1999', width=0.3)
I could use a scatter plot, for example, and both charts would coexist, and in some cases overlap (if the data is the same), but I was really aiming at plotting it side by side. The other answers related to the subject usually have older versions of Bokeh with deprecated functions.
Any way I can solve this? Thanks!
Edit:
Here is the .head() method. The other one will return exactly the same categories, columns and rows, except that obviously the data changes since it's from a different season.
Tm W L W-L% PF PA PD MoV SoS SRS OSRS \
0 Washington Redskins 10 6 0.625 443 377 66 4.1 -1.3 2.9 6.8
1 Dallas Cowboys 8 8 0.500 352 276 76 4.8 -1.6 3.1 -0.3
2 New York Giants 7 9 0.438 299 358 -59 -3.7 0.7 -3.0 -1.8
3 Arizona Cardinals 6 10 0.375 245 382 -137 -8.6 -0.2 -8.8 -5.5
4 Philadelphia Eagles 5 11 0.313 272 357 -85 -5.3 1.1 -4.2 -3.3
DSRS
0 -3.9
1 3.4
2 -1.2
3 -3.2
4 -0.9
And the value of executing just x=dodge returns:
dodge() missing 1 required positional argument: 'value'
By adding that argumento value=0.0 or value=0.2 the error returned is the same as the original post.
The first argument to dodge should a single column name of a column in a ColumnDataSource. The effect is then that any values from that column are dodged by the specified amount when used as coordinates.
You are trying to pass the contents of a column, which is is not expected. It's hard to say for sure without complete code to test, but you most likely want
x=dodge('Tm', ...)
However, you will also need to actually use an explicit Bokeh ColumnDataSource and pass that as source to vbar as is done in the example you link. You can construct one explicitly, but often times you can also just pass the dataframe directly source=df, and it will be adapted.
Convert .txt file into multi index dataframe pandas
I have a very unorganized dataset located in a text file say file.txt
The sample looks something like so
TYPE Invoice C AC DATE TIME Total Invoice Qty1 ITEMVG By Total 3,000.00
Piece Item
5696 01/03/2018 09:21 32,501.35 1 Golden Plate ÞÔÞæÇä ÈÞÑ 6,517.52
1 áÈä ÑæÇÈí ÊÚäÇíá 2 ßÛ 4,261.45
1 Magic chef pop corn 907g 3,509.43
1 áÈäÉ ÊÚäÇíá ÔÝÇÝÉ 1 ßíáæ 9,525.60
1 KHOURY UHT 1 L 2,506.74
1 ÎÈÒ ÔãÓíä ÕÛíÑ 1,002.69
2 Almera 200Tiss 2,506.74
1.55 VG Potato 1,550.17
0.41 VG Eggplant 619.67
1 Delivery Charge 501.35
5697 01/03/2018 09:31 15,751.35 0.5 Halloum 1K. 4,476.03
0.59 Cheese double Cream 3,253.75
3 ãæáÇä ÏæÑ ÎÈÒ æÓØ 32 3,760.11
3 ãæáÇä ÏæÑ ÎÈÒ æÓØ 32 3,760.11
1 Delivery Charge 501.35
I want to import it into a data frame pandas using multi-index. Can someone help me with this?
In fact it can not read it as a txt file
# Obtain the Unorganized data from txt
file1=open('file.txt','r')
UnOrgan=file1.read()
You should be able to just read it in using read_table. import pandas as pd df = pd.read_table(<your file>, sep="\t", headers=[rows with column info]) I'm guessing that the separator is a tab.
Multi Criterion Max If Statement
My dataset looks like this... State Close Date Probability Highest Prob/State WA 12/31/2016 50% FALSE WA 12/19/2016 80% FALSE WA 10/15/2016 80% TRUE My objective is to build a formula to populate the right-most column. The formula should assess Close Dates and Probabilities within each state. First, it should select the highest probability, then it should select the nearest close date if there is a tie on probability (as in the example). For that record, it should read "TRUE". I assume this would include a MAX IF statement but haven't been able to get it to work. Here is a more robust set of data I'm working with. It may actually be easier to first find the highest probability within each Region then select the minimum (oldest) date if there is a tie on probability. This too will serve my purposes. Region Forecast Close Date Probability (%) Okeechobee FL 6/27/2016 90 Okeechobee West FL 7/1/2016 40 Albany GA 3/11/2016 100 Emerald Coast FL 6/30/2016 60 Emerald Coast FL 10/1/2016 40 Cullman_Hartselle TN 4/30/2016 10 North MS 10/1/2016 25 Roanoke VA 8/31/2016 25 Roanoke VA 8/1/2016 40 Gardena CA 6/1/2016 80 Gardena CA 6/1/2016 80 Lomita-Harbor City 6/30/2016 60 Lomita-Harbor City 6/30/2016 0 Lomita-Harbor City 6/30/2016 40 Eastern NC 6/30/2016 60 Northwest NC 9/16/2016 10 Fort Collins_Greeley CO 3/1/2016 100 Northwest OK 6/30/2016 100 Southwest MO 7/29/2016 90 Northern NH-VT 3/1/2016 20 South DE 12/1/2016 0 South DE 12/1/2016 20 Kingston NY 12/30/2016 5 Longview WA 11/30/2016 5 North DE 12/1/2016 20 North DE 12/1/2016 0 Salt Lake City UT 8/31/2016 20 Idaho Panhandle 8/26/2016 0 Bridgeton_Salem NJ 7/1/2016 25 Bridgeton_Salem NJ 7/1/2016 65 Layton_Ogden UT 3/25/2016 5 Central OR 6/30/2016 10
The following Array formula should work:
=(ABS(B2-$F$2)=MIN(IF(($A$2:$A$33=A2)*(C2=MAX(IF($A$2:$A$33=A2,$C$2:$C$33))),ABS($B$2:$B$33-$F$2))))*(C2=MAX(IF($A$2:$A$33=A2,$C$2:$C$33)))>0
Being an array formula use Ctrl-Shift-Enter when exiting Edit mode. If done properly Excel will put {} around the formula.
Edit
Added #tigeravatar suggestion to avoid volatile functions.
I think this is OK now but needs to be checked against the more complete set of data provided by OP. It counts:- (1) Any rows with same state but higher probability (2) Any rows with same state and probability, in the future (or present) and nearer to today's date (3) Any rows with same state and probability, in the past and nearer to today's date. If all these are zero, you should have the right one. =COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,">"&$C2) +COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,$C2,$B$2:$B$100,"<"&$G$2+IF ($B2>=$G$2,DATEDIF($G$2,$B2,"d"),DATEDIF($B2,$G$2,"d")),$B$2:$B$100,">="&$G$2) +COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,$C2,$B$2:$B$100,">"&$G$2-IF($B2>=$G$2,DATEDIF($G$2,$B2,"d"),DATEDIF($B2,$G$2,"d")),$B$2:$B$100,"<"&$G$2) =0 If the dates are all in the future, it can be simplified a lot:- =COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,">"&$C2) +COUNTIFS($A$2:$A$100,$A2,$C$2:$C$100,$C2,$B$2:$B$100,"<"&$G$2+DATEDIF($G$2,$B2,"d")) =0