Hi, and welcome!
Please see the FAQ: What's a reproducible example (`reprex`) and how do I create one? Using a reprex, complete with representative data will attract quicker and more answers. And also check the homework policy, please.
Without really having the data, the best advice I can give is an example of how a histogram is supposed to work
set.seed(14)
x <- rchisq(100, df = 4)
x
#> [1] 1.5978282 3.3322985 3.0708725 2.5744330 6.7764815 2.8431800
#> [7] 4.7798098 4.2013360 3.6203090 2.5236530 4.8788430 2.3256201
#> [13] 10.1759434 2.8153700 0.6993601 2.7190979 2.3547836 4.3194835
#> [19] 4.3472164 3.7375415 5.0207279 4.1526903 2.1998894 3.6858705
#> [25] 4.5662583 3.8839883 3.9807882 0.9231033 3.1015811 2.8566852
#> [31] 1.8023261 1.2103736 7.4775292 2.9779815 2.1628704 1.3421543
#> [37] 3.2563822 1.5077376 2.5180166 1.4114212 0.8293910 7.6368595
#> [43] 16.6302925 2.2744868 1.7719876 0.4947304 1.7639663 5.3714693
#> [49] 1.6524618 7.0119613 16.9767672 3.2143291 1.6203122 6.5253462
#> [55] 1.0580171 4.8303820 2.8667919 3.6738743 2.4885080 8.0107460
#> [61] 2.5245266 1.0493424 3.0705241 15.4316212 0.3453903 7.0859825
#> [67] 1.7329998 2.0512795 1.3071472 5.6344011 3.9541127 2.6325437
#> [73] 0.3115387 5.2884788 1.3369640 5.0583443 3.4252851 4.1332816
#> [79] 2.9293921 1.4299040 3.0021506 1.5113295 1.5828157 2.5553601
#> [85] 1.2886474 3.9494644 1.4949560 2.0846314 3.1832552 5.2421299
#> [91] 4.3031409 1.8940315 1.9225727 3.9824388 2.8678671 5.6737469
#> [97] 11.4091608 4.0284655 3.3840483 6.8884167
hist(x)
Created on 2020-03-30 by the reprex package (v0.3.0)