Correlation in Dataset and grouping the data by teams and Year

General
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1

I have multiple .csv files for months. Below is a sample for one month.

Output - I need to merge all the .csv files and put a month value for each row in the file and then merge the data of multiple sheets.
Post that I would like to find the correlation in the data by Team and Month for any two selected variable in the data.

Input -

Team_Name IDWwMember Resources Workout Volume Diverted Downtime Time_Worked Core_Time Staff_Complement Annual_Leave Temporary_Staff Overtime Borrowed Loaned Flexitime OneOnOne System numberOfCreatedMonths numberOfTeamTenureMonths
A 30406 12750 5850 122 1355 12750 11395 14790 0 0 510 0 2550 0 30 220 57.3 3.81
A 33185 14340 11910 257 1325 1275 13065 11740 14790 1020 0 570 0 0 0 30 710 41.43 22.51
A 33188 10200 10380 208 400 10200 9800 14790 5100 0 510 0 0 0 30 41.43 26.97
A 21052 14025 7800 161 700 3315 10710 10010 14790 765 0 0 0 0 0 30 150 88.68 1.97
A 32506 16320 13560 291 2075 1020 15300 13225 14790 0 0 1530 0 0 0 30 670 44.75 33.74
A 25834 14535 8250 166 1255 1530 13005 11750 14790 765 0 510 0 0 0 30 72.74 1.74
A 24714 15240 9420 204 880 510 14730 13850 14790 0 0 570 0 120 0 30 240 77.08 1.74
A 25420 12960 5490 111 1850 510 12450 10600 14790 510 0 1590 0 2910 0 30 710 74.28 1.74
A 24185 15300 8550 176 1295 2550 12750 11455 14790 0 0 510 0 0 0 30 90 78.75 1.74
A 33181 15360 12720 290 2209 15360 13151 14790 0 0 1080 0 510 0 50 698 41.43 22.51
A 33759 15360 10440 219 3170 1800 13560 10390 14790 510 0 1080 0 0 0 30 1960 38.93 11.96
A 32174 15615 12600 279 3265 510 15105 11840 14790 0 0 825 0 0 0 30 255 47.28 47.25
A 33724 13320 6900 145 1605 13320 11715 14790 1530 0 1080 0 1020 0 30 300 39 1.74
A 12077 13590 6930 139 700 510 13080 12380 14790 1530 0 330 0 0 0 30 60 117.09 1.74
A 14411 13065 4800 103 1190 2295 10770 9580 14790 255 0 1080 0 2550 0 30 690 110.29 1.74
A 32502 14025 6030 138 515 7140 6885 6370 14790 765 0 0 0 0 0 30 180 44.75 33.84
A 35017 12289 8670 189 1100 2040 10249 9149 14790 3060 0 510 0 0 49 30 525 33.12 22.51
A 33187 15411 13140 301 1165 510 14901 13736 14790 0 0 570 0 0 51 30 540 41.43 26.97
A 24276 3825 1290 25 545 3825 3280 7650 765 0 0 0 3060 0 30 78.26 1.41
B 18900 4905 2250 62 751 4905 4154 7650 0 0 510 0 3255 0 45 121 97.09 31.54
B 22521 15600 5847 150 3669 1020 14580 10911 14790 1020 0 1830 0 0 0 75 542 83.98 48.76
B 27462 15300 4680 111 3696 1140 14160 10464 14790 0 0 510 0 0 0 98 1424 68.37 1.97
B 35443 15810 6948 154 2300 35 15775 13475 14790 510 0 1530 0 0 0 90 910 31.11 8.25
B 30322 14790 3300 77 1158 7680 7110 5952 14790 0 0 0 0 0 0 30 513 57.46 6.37
B 14572 12240 3828 92 2819 1020 11220 8401 14790 510 0 510 0 2550 0 20 1170 109.77 30
B 35447 14280 6450 147 2156 14280 12124 14790 1530 0 1020 0 0 0 54 847 31.11 8.25
B 30843 3375 1080 31 1147 3375 2228 7650 1020 0 510 0 3765 0 439 55.33 34.04
C 35021 16320 5931 157 1681 16320 14639 14790 0 0 1530 0 0 0 30 661 33.12 1.28
C 28128 16320 6024 173 1350 16320 14970 14790 0 0 1530 0 0 0 30 300 65.61 1.51
C 35020 15810 5464 138 1275 15810 14535 14790 510 0 1530 0 0 0 30 361 33.12 1.28
C 26318 15300 5382 148 1648 510 14790 13142 14790 510 0 1020 0 0 0 30 525 71.56 2.04

Output

Team Month Cor workout: Coretime Cor WorkOut : Timeworked
A Jan -0.19 0.49
A Feb 0.69 -0.38
A Mar 0.22 0.96
B Jan -0.38 0.23
B Feb 0.08 -0.72
B Mar 0.38 0.53
C Jan -0.37 0.65
C Feb -0.51 -0.37
C Mar 0.47 0.56
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