grapher/assets/Student_list.csv

1	First Name	Last Name	Sex	Tutorial 1	Tutorial 2	Extended Applications	Numpy & MatPlotLib	SciPy	Monte Carlo	Pandas & Seaborn	Folium
2	Abdalaziz	Abunjaila	Male	30.5	15	18	28	17	17	17	22
3	Marleen	Adolphi	Female	29.5	15	18	32	19	0	17	24
4	Aurela	Brahimi	Female	17.5	15	15.5	26	16	17	19	16
5	Cam Thu	Do	Female	31	15	18	34	19	20	21.5	22
6	Nova	Eib	Female	31	15	15	34	20	20	21	27
7	Nele	Grundke	Female	23.5	13	16	28	20	17	21	18
8	Anna	Grünewald	Female	12	14	16	29	16	15	19	9
9	Yannik	Haupt	Male	18	6	14	21	13	2	9	0
10	Janna	Heiny	Female	30	15	18	33	18	20	22	25
11	Milena	Krieger	Female	30	15	18	33	20	20	21.5	26
12	Julia	Limbach	Female	27.5	12	18	29	11	19	17.5	26
13	Viktoria	Litza	Female	21.5	15	18	27	13	20	22	21
14	Manthey	Leonie	Female	28.5	14	18	29	20	10	18	23
15	Izabel	Mike	Female	29.5	15	15	35	11	4	19	21
16	Lea	Noglik	Female	22.5	15	17	34	13	10	20	0
17	Donika	Nuhiu	Female	31	13.5	18	35	14	10	17	18
18	Julia	Renner	Female	27.5	10	14	0	20	17	11	20
19	Fabian	Rothberger	Male	30.5	15	18	34	17	17	19	22
20	Natascha	Rott	Female	29.5	12	18	32	19	20	21	26
21	Isabel	Rudolf	Female	27.5	9	17	34	16	19	19	21
22	Melina	Sablotny	Female	31	15	18	33	20	20	21	19
23	Alea	Schleier	Female	27	14	18	34	16	18	21.5	22
24	Flemming	Schur	Male	29.5	15	17	34	19	20	19	22
25	Marie	Seeger	Female	27.5	15	18	32	14	9	17	22
26	Lucy	Thiele	Female	27.5	15	18	27	20	17	19	18
27	Lara	Troschke	Female	28.5	14	17	28	13	19	21	25
28	Inga-Brit	Turschner	Female	25.5	14	18	34	20	16	19	22
29	Alea	Unger	Female	30	12	18	31	20	20	21	22
30	Marie	Wallbaum	Female	28.5	14	18	34	17	20	19	24
31	Katharina	Walz	Female	31	15	18	31	19	19	17	24
32	Xiaowei	Wang	Male	30.5	14	18	26	19	17	0	0
33	Lilly-Lu	Warnken	Female	30	15	18	30	14	17	19	14