Hi, and welcome!
Unfortunately, screenshots are seldom useful. The the FAQ: What's a reproducible example (`reprex`) and how do I do one? for how to post code that can be worked with to help find solutions.
From what I can make out, there's probably an easier way to approach this. I'll used a ginned up data frame.
suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(tibble))
dat <- structure(list(state = structure(c(3L, 4L, 4L, 32L, 21L, 47L,
37L, 25L, 22L, 14L, 38L, 26L, 35L, 37L, 39L, 6L, 5L, 15L, 32L,
5L, 19L, 43L, 1L, 8L, 32L, 49L, 41L, 6L, 37L, 34L, 43L, 15L,
16L, 19L, 24L, 25L, 8L, 49L, 29L, 22L, 18L, 24L, 36L, 28L, 37L,
16L, 26L, 28L, 30L, 43L, 9L, 18L, 25L, 13L, 45L, 12L, 3L, 3L,
44L, 32L, 24L, 40L, 8L, 20L, 13L, 28L, 36L, 35L, 45L, 6L, 21L,
31L, 13L, 14L, 47L, 21L, 48L, 30L, 43L, 6L, 2L, 35L, 49L, 9L,
7L, 26L, 23L, 19L, 2L, 8L, 42L, 2L, 9L, 14L, 25L, 24L, 49L, 49L,
36L, 28L, 7L, 23L, 3L, 21L, 31L, 10L, 4L, 36L, 11L, 49L, 4L,
34L, 19L, 31L, 12L, 32L, 36L, 25L, 43L, 21L, 38L, 6L, 21L, 19L,
5L, 5L, 15L, 33L, 1L, 26L, 34L, 6L, 5L, 37L, 14L, 37L, 47L, 25L,
10L, 40L, 4L, 15L, 4L, 21L, 30L, 27L, 49L, 43L, 11L, 15L, 46L,
8L, 48L, 48L, 3L, 36L, 9L, 32L, 18L, 4L, 15L, 45L, 33L, 23L,
49L, 8L, 35L, 30L, 38L, 48L, 47L, 42L, 48L, 5L, 14L, 37L, 42L,
37L, 24L, 2L, 32L, 12L, 27L, 35L, 25L, 15L, 14L, 47L, 45L, 30L,
48L, 15L, 9L, 48L, 17L, 41L, 31L, 24L, 8L, 21L), .Label = c("Alabama",
"Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut",
"Delaware", "Florida", "Georgia", "Hawaii", "Idaho", "Illinois",
"Indiana", "Iowa", "Kentucky", "Louisiana", "Maine", "Maryland",
"Massachusetts", "Michigan", "Minnesota", "Mississippi", "Missouri",
"Montana", "Nebraska", "Nevada", "New Hampshire", "New Jersey",
"New Mexico", "New York", "North Carolina", "North Dakota", "Ohio",
"Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", "South Carolina",
"South Dakota", "Tennessee", "Texas", "Utah", "Vermont", "Virginia",
"Washington", "West Virginia", "Wisconsin", "Wyoming"), class = "factor"),
value = c(-0.0500677443851305, 0.20255093214272, -0.0382925606590059,
0.842050361189436, -0.798877956145816, -1.68232262518171,
0.728528650817833, 0.985837774682992, -1.70765697177937,
-0.160038596640867, 0.721607555842305, -0.4248095669316,
-0.0703716536202222, -0.515441373220822, -0.607659593956769,
0.590966244196858, 1.86541615611373, -0.624304007042872,
-0.260559170248893, 0.477814052255288, 1.27905182861303,
-0.96650997514641, -0.237572682646222, -0.337335716976861,
-2.46684945494161, 0.379837468880197, 0.0479904475705669,
0.563291104064344, 2.79454126780037, -0.466727682824244,
0.351165429744233, -0.259014297080849, 0.818619520037089,
-0.34885583004204, -0.880288189545205, -1.40547491665107,
-1.45708474221557, -0.271348203185227, -0.567222081707831,
0.491802786691456, 0.523967396376311, -0.193056996050934,
-0.224085896962664, 0.76573609838597, 1.13803008018725, 0.479745435828822,
1.45876122753945, -0.606953343622046, -0.740195778932835,
0.702650578965198, 0.903451986901155, -1.98448698066832,
-0.380139159867896, 1.43071408223918, 0.683328381180665,
-0.166913190856337, 0.0290560992653911, 0.811006738923476,
-0.366284863022354, -0.158016909103811, -2.11491634120928,
0.0800326394051908, 2.47630292748179, 0.62804240658866, 1.31059533789514,
1.58070018846522, -0.11322893024015, -0.433243197890605,
-0.433427603946357, -0.266666798889549, -0.233472482656319,
-1.60584401126863, -0.497343252452946, 1.07321951886125,
1.65431644426522, 0.924410502730337, -0.946163234285948,
0.744153019223842, 0.00721400339231964, 1.46910032266189,
0.300756875443599, 0.654827473013311, 0.447282537200565,
0.198008075524172, 0.00272492792992627, 0.993493754991008,
-0.385509051871126, -1.39073532351034, -1.50354727359961,
0.363942036412502, -0.933791292753043, 0.406834143748693,
-0.871559521243467, 0.797215614539181, 0.51753723350601,
0.732315117561597, 0.935782091055621, -0.0550377824545726,
1.77278859549965, -0.279975296434756, 0.512370288463287,
-0.128210402608692, -1.28007807753721, 0.666832961080878,
2.15033426091563, -0.240325127373937, 0.533136353514523,
-1.17385341594897, -1.24759543922249, -0.745768551818649,
0.248801955741311, 2.23608795312034, 0.0183359430283382,
0.440517156987265, -0.148848607579916, -0.432521774404884,
-1.66773631329721, 0.0675303269311713, -1.3297403826819,
0.338087598917726, -1.309815173351, 0.376571528646985, -1.34854528863469,
-0.123685528729531, -0.322133225839523, 0.84498816880702,
-0.873845088212342, -1.14074972669784, 0.960735294993471,
-0.487958264823631, 0.139626542824682, -0.749470294124344,
-0.997451660816324, 0.627275462152485, -0.836795958009802,
-0.845384452185865, 0.473223313355319, -0.186090958461863,
-0.891841975841899, 0.290483013894842, -1.54379348670249,
-1.11239148851224, 0.0217500342544884, 1.19832600460642,
0.98637741869489, 0.123466367191884, 0.597525075104177, 1.20983208255003,
0.496663997562984, 0.118392153581365, 0.535587807449442,
-1.80132661047085, -1.33625393567737, -0.693801148653181,
2.22266801758049, -1.14194171179068, 1.75957260962327, 0.284299765142467,
-0.916690887327047, 0.408561928862153, 0.837167055885323,
0.13663146471077, -1.7563743405609, 1.42341426043586, 0.169619995438837,
0.07903738540465, -0.618575685858797, 0.446159034278656,
-0.484526978038261, 0.321365505018176, 2.66194356635818,
2.01755421655406, 0.77523363771253, -0.95119697165064, 0.0811268241562798,
0.132201773876715, -0.698220813180683, -0.597477948270436,
0.977161860307835, -1.60480321495488, 0.50239474407725, -0.332805841859567,
0.540906667423175, 1.26119500623883, -0.795664250968672,
-1.20337244011018, -1.8190536943728, -0.723954827343716,
0.566651110548388, 0.0474640275314466, -0.541894247448819,
0.549433863347651, -1.30340209870227, 0.39105018129508, -0.72690419482481,
-1.3745366236515, -0.0189437262104834, -0.0974762970313,
-1.13939758440753, -4.2893577979456)), row.names = c(NA,
-200L), class = c("tbl_df", "tbl", "data.frame"))
dat %>% mutate(lone_star = ifelse(state == "Texas",1,0)) -> results
results %>% filter(lone_star == 1)
#> # A tibble: 3 x 3
#> state value lone_star
#> <fct> <dbl> <dbl>
#> 1 Texas -0.934 1
#> 2 Texas 2.02 1
#> 3 Texas -0.698 1
Created on 2020-02-13 by the reprex package (v0.3.0)