title: Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) 0 non-na cases
body: <p>I have already checked the other questions with on this issue, but since the problem seems to be very specific they weren't helpful.</p>
  
  <p>I have a dataframe like this (this is just a quick example, example data from dput() is provided below):</p>
  
  <pre><code>year species abundance site county
  2005 A       2         SH1  Göttingen
  2006 A       0         SH1  Göttingen
  2007 A       NA        SH1  Göttingen
  2008 A       2         SH1  Göttingen
  2009 A       NA        SH1  Göttingen
  2010 A       2         SH1  Göttingen
  2011 A       NA        SH1  Göttingen
  2005 B       2         SH1  Göttingen
  2006 B       0         SH1  Göttingen
  2007 B       NA        SH1  Göttingen
  2008 B       2         SH1  Göttingen
  2009 B       NA        SH1  Göttingen
  2010 B       2         SH1  Göttingen
  2011 B       NA        SH1  Göttingen
  2005 A       2         SH1  Göttingen
  2006 A       0         SH1  Göttingen
  2007 A       NA        SH1  Göttingen
  2008 A       2         SH1  Göttingen
  2009 A       NA        SH1  Göttingen
  2010 A       2         SH1  Göttingen
  2011 A       NA        SH1  Göttingen
  2005 A       2         SH2  Göttingen
  2006 A       0         SH2  Göttingen
  2007 A       NA        SH2  Göttingen
  2008 A       2         SH2  Göttingen
  2009 A       NA        SH2  Göttingen
  2010 A       2         SH2  Göttingen
  2011 A       NA        SH2  Göttingen
  </code></pre>
  
  <p>It contains the abundance for 11 species on several different sites per county (more than 1500 sites in over 400ish counties) for each year 2005-2011. for each site, in every county, every year, all species have been accounted for, so there is either an NA, or a number in abundance for every year. The number of sites varies per county.</p>
  
  <p>I would like to run the following loop to put the abundance into several columns: It should create a linear model to calculate population trends over these years and put the output in an additional row. In the end I would like to have a trend for every species on every site over the years:</p>
  
  <pre><code>alldata_lm$slope_abundance_plot &lt;- NA
  alldata_lm$p_slope_abundance_plot &lt;- NA
  
  species &lt;- unique(alldata_lm$species)
  sites &lt;- unique(alldata_lm$site)
  
  for (i in (1:length(species))) {
    for (k in(1:length(sites))) {        
      print(c(i,k))
      lm1 &lt;-  lm(abundance ~ year, data = alldata_lm[alldata_lm$species == species[i] &amp; alldata_lm$site == sites[k],], na.action=na.omit)
      alldata_lm$slope_abundance_plot[alldata_lm$species == species[i] &amp; alldata_lm$site == sites[k]] &lt;- coefficients(lm1)[2]
      if (nrow(coef(summary(lm1)))&gt;1){ alldata_lm$p_slope_abundance_plot[alldata_lm$species == species[i] &amp; alldata_lm$site == sites[k]] &lt;- coef(summary(lm1))[2,4]}
    }  
  }
  </code></pre>
  
  <p>However, when I do, it returns the following error:</p>
  
  <pre><code>Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 
    alle Fälle NA
  </code></pre>
  
  <p>The same loop works perfectly with a very similar dataframe, the only difference is that the current dataframe contains far more NA's. </p>
  
  <p>Deleting the NA's prior to running the loop does not help. I get the error message no matter if there are any NA's in the abundance column or not. I think the error might occur somewhere else. The year column does never contain any missing values.</p>
  
  <p>I'd greatly appreciate any help! Thanks</p>
  
  <p>EXAMPLE DATA</p>
  
  <pre><code> structure(list(site = structure(c(700L, 700L, 700L, 700L, 700L, 
  700L, 700L), .Label = c("bb1", "bb100", "bb101", "bb104", "bb107", 
  "bb108", "bb109", "bb11", "bb111", "bb113", "bb115", "bb116", 
  "bb117", "bb118", "bb119", "bb120", "bb121", "bb122", "bb123", 
  "bb124", "bb125", "bb126", "bb127", "bb129", "bb130", "bb131", 
  "bb132", "bb134", "bb135", "bb138", "bb139", "bb14", "bb140", 
  "bb143", "bb147", "bb15", "bb150", "bb152", "bb154", "bb155", 
  "bb156", "bb157", "bb158", "bb159", "bb163", "bb164", "bb166", 
  "bb167", "bb169", "bb170", "bb171", "bb172", "bb173", "bb174", 
  "bb175", "bb176", "bb177", "bb178", "bb179", "bb180", "bb181", 
  "bb183", "bb186", "bb187", "bb188", "bb19", "bb191", "bb192", 
  "bb193", "bb194", "bb197", "bb198", "bb199", "bb20", "bb200", 
  "bb201", "bb202", "bb203", "bb204", "bb205", "bb207", "bb208", 
  "bb209", "bb21", "bb210", "bb211", "bb212", "bb213", "bb215", 
  "bb216", "bb217", "bb218", "bb219", "bb220", "bb221", "bb224", 
  "bb225", "bb228", "bb23", "bb230", "bb232", "bb234", "bb237", 
  "bb239", "bb242", "bb27", "bb32", "bb35", "bb37", "bb38", "bb39", 
  "bb4", "bb40", "bb41", "bb47", "bb49", "bb53", "bb55", "bb58", 
  "bb59", "bb6", "bb60", "bb63", "bb65", "bb66", "bb7", "bb70", 
  "bb72", "bb73", "bb76", "bb77", "bb79", "bb8", "bb80", "bb81", 
  "bb82", "bb84", "bb85", "bb87", "bb89", "bb9", "bb90", "bb91", 
  "bb92", "bb93", "bb94", "bb96", "bb97", "bb98", "be14", "be15", 
  "be17", "be30", "bw10", "bw100", "bw104", "bw108", "bw111", "bw112", 
  "bw12", "bw120", "bw124", "bw126", "bw13", "bw144", "bw146", 
  "bw175", "bw183", "bw192", "bw193", "bw198", "bw199", "bw200", 
  "bw202", "bw208", "bw210", "bw211", "bw213", "bw215", "bw219", 
  "bw225", "bw226", "bw229", "bw236", "bw243", "bw257", "bw262", 
  "bw266", "bw268", "bw283", "bw294", "bw3", "bw30", "bw307", "bw326", 
  "bw327", "bw338", "bw339", "bw341", "bw35", "bw36", "bw360", 
  "bw368", "bw380", "bw381", "bw397", "bw405", "bw42", "bw53", 
  "bw58", "bw6", "bw7", "bw84", "bw89", "bw91", "bw92", "bw96", 
  "bw97", "by10", "by103", "by109", "by11", "by110", "by111", "by112", 
  "by113", "by114", "by115", "by116", "by117", "by118", "by120", 
  "by122", "by125", "by126", "by127", "by128", "by129", "by130", 
  "by134", "by137", "by14", "by142", "by144", "by146", "by147", 
  "by150", "by151", "by152", "by153", "by154", "by155", "by156", 
  "by157", "by158", "by159", "by163", "by164", "by166", "by167", 
  "by169", "by170", "by171", "by173", "by175", "by176", "by177", 
  "by178", "by18", "by180", "by182", "by186", "by187", "by188", 
  "by19", "by192", "by193", "by194", "by197", "by200", "by203", 
  "by205", "by210", "by212", "by215", "by22", "by222", "by223", 
  "by225", "by226", "by229", "by230", "by231", "by233", "by234", 
  "by236", "by238", "by239", "by24", "by240", "by241", "by242", 
  "by243", "by247", "by248", "by25", "by250", "by251", "by255", 
  "by257", "by267", "by268", "by271", "by272", "by274", "by275", 
  "by278", "by279", "by28", "by280", "by283", "by284", "by285", 
  "by286", "by287", "by289", "by29", "by290", "by291", "by292", 
  "by293", "by294", "by295", "by298", "by30", "by303", "by305", 
  "by307", "by308", "by310", "by32", "by321", "by322", "by323", 
  "by324", "by326", "by331", "by333", "by334", "by337", "by34", 
  "by341", "by346", "by347", "by350", "by352", "by356", "by357", 
  "by36", "by368", "by37", "by370", "by376", "by378", "by39", "by4", 
  "by40", "by41", "by43", "by451", "by452", "by47", "by5", "by52", 
  "by53", "by56", "by63", "by64", "by65", "by66", "by67", "by68", 
  "by69", "by7", "by72", "by74", "by76", "by79", "by8", "by80", 
  "by87", "by88", "by89", "by90", "by91", "by92", "by96", "by97", 
  "by98", "hb16", "hb17", "hb18", "hb21", "hb30", "hb5", "hb6", 
  "hb7", "hb9", "he100", "he103", "he106", "he107", "he108", "he109", 
  "he110", "he111", "he113", "he114", "he115", "he116", "he119", 
  "he120", "he122", "he124", "he13", "he130", "he137", "he14", 
  "he144", "he145", "he150", "he154", "he18", "he37", "he42", "he46", 
  "he47", "he51", "he52", "he66", "he68", "he7", "he70", "he72", 
  "he73", "he75", "he82", "he83", "he84", "he85", "he89", "he9", 
  "he91", "he93", "he94", "he96", "he97", "hh10", "hh28", "hh29", 
  "hh30", "hh41", "hh44", "mv108", "mv109", "mv110", "mv122", "mv124", 
  "mv125", "mv126", "mv141", "mv143", "mv15", "mv153", "mv156", 
  "mv160", "mv17", "mv24", "mv29", "mv40", "mv41", "mv50", "mv55", 
  "mv61", "mv63", "mv76", "mv82", "ni10", "ni100", "ni101", "ni102", 
  "ni11", "ni110", "ni111", "ni119", "ni122", "ni125", "ni126", 
  "ni13", "ni131", "ni134", "ni135", "ni136", "ni138", "ni14", 
  "ni142", "ni146", "ni147", "ni149", "ni15", "ni150", "ni152", 
  "ni162", "ni163", "ni166", "ni167", "ni168", "ni169", "ni170", 
  "ni171", "ni172", "ni175", "ni182", "ni187", "ni188", "ni189", 
  "ni191", "ni192", "ni193", "ni198", "ni2", "ni20", "ni206", "ni215", 
  "ni218", "ni225", "ni226", "ni227", "ni231", "ni236", "ni239", 
  "ni240", "ni241", "ni242", "ni243", "ni244", "ni246", "ni252", 
  "ni257", "ni26", "ni260", "ni263", "ni272", "ni274", "ni282", 
  "ni286", "ni290", "ni291", "ni297", "ni298", "ni299", "ni3", 
  "ni303", "ni32", "ni34", "ni37", "ni38", "ni39", "ni4", "ni40", 
  "ni41", "ni43", "ni45", "ni453", "ni455", "ni46", "ni47", "ni49", 
  "ni50", "ni52", "ni55", "ni6", "ni61", "ni63", "ni66", "ni68", 
  "ni71", "ni72", "ni73", "ni76", "ni77", "ni85", "ni87", "ni88", 
  "ni89", "ni90", "ni91", "ni92", "ni93", "ni95", "ni97", "nw10", 
  "nw108", "nw110", "nw112", "nw126", "nw13", "nw130", "nw140", 
  "nw142", "nw143", "nw149", "nw154", "nw156", "nw173", "nw182", 
  "nw20", "nw25", "nw38", "nw41", "nw5", "nw50", "nw52", "nw53", 
  "nw54", "nw55", "nw6", "nw60", "nw63", "nw7", "nw72", "nw73", 
  "nw74", "nw84", "nw86", "nw92", "rp101", "rp102", "rp103", "rp106", 
  "rp108", "rp109", "rp116", "rp117", "rp120", "rp130", "rp131", 
  "rp139", "rp140", "rp143", "rp144", "rp146", "rp21", "rp22", 
  "rp23", "rp24", "rp36", "rp4", "rp84", "rp94", "rp99", "sh100", 
  "sh101", "sh102", "sh103", "sh106", "sh109", "sh11", "sh111", 
  "sh112", "sh117", "sh12", "sh121", "sh123", "sh125", "sh128", 
  "sh130", "sh132", "sh14", "sh140", "sh17", "sh18", "sh19", "sh20", 
  "sh25", "sh26", "sh27", "sh30", "sh33", "sh34", "sh35", "sh36", 
  "sh37", "sh39", "sh42", "sh43", "sh44", "sh45", "sh46", "sh47", 
  "sh51", "sh52", "sh54", "sh55", "sh58", "sh59", "sh60", "sh61", 
  "sh62", "sh63", "sh65", "sh66", "sh67", "sh69", "sh70", "sh71", 
  "sh72", "sh73", "sh74", "sh75", "sh76", "sh78", "sh79", "sh8", 
  "sh84", "sh86", "sh88", "sh89", "sh91", "sh93", "sh95", "sh96", 
  "sh98", "sh99", "sn104", "sn112", "sn117", "sn120", "sn123", 
  "sn131", "sn141", "sn144", "sn145", "sn15", "sn151", "sn158", 
  "sn159", "sn16", "sn162", "sn164", "sn165", "sn167", "sn18", 
  "sn25", "sn27", "sn28", "sn30", "sn35", "sn40", "sn44", "sn45", 
  "sn5", "sn56", "sn69", "sn7", "sn72", "sn74", "sn79", "sn83", 
  "sn87", "sn89", "sn9", "sn91", "sn92", "sn93", "sn99", "st1", 
  "st100", "st101", "st103", "st105", "st107", "st108", "st109", 
  "st11", "st110", "st111", "st112", "st113", "st114", "st115", 
  "st116", "st118", "st119", "st120", "st121", "st125", "st126", 
  "st127", "st13", "st130", "st134", "st135", "st137", "st139", 
  "st140", "st141", "st143", "st144", "st145", "st146", "st147", 
  "st148", "st150", "st151", "st153", "st158", "st159", "st160", 
  "st162", "st166", "st21", "st24", "st25", "st26", "st27", "st28", 
  "st30", "st33", "st34", "st4", "st43", "st47", "st49", "st50", 
  "st55", "st56", "st57", "st59", "st60", "st61", "st64", "st69", 
  "st70", "st72", "st75", "st77", "st79", "st84", "st87", "st88", 
  "st91", "st92", "st97", "st98", "st99", "th100", "th103", "th104", 
  "th105", "th112", "th118", "th121", "th123", "th15", "th16", 
  "th18", "th19", "th20", "th22", "th26", "th27", "th31", "th32", 
  "th36", "th39", "th4", "th40", "th44", "th45", "th49", "th50", 
  "th51", "th52", "th55", "th56", "th58", "th59", "th60", "th61", 
  "th63", "th64", "th73", "th76", "th8", "th81", "th83", "th85", 
  "th91", "th94", "th95", "th96", "th98", "th99"), class = "factor"), 
      year = 2005:2011, species = structure(c(8L, 8L, 8L, 8L, 8L, 
      8L, 8L), .Label = c("common linnet", "common whitethroat", 
      "corn bunting", "eurasian skylark", "northern lapwing", "red-backed shrike", 
      "tree sparrow", "western yellow wagtail", "whinchat", "woodlark", 
      "yellowhammer"), class = "factor"), abundance = c(NA_integer_, 
      NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_, 
      NA_integer_), county = structure(c(48L, 48L, 48L, 48L, 48L, 
      48L, 48L), .Label = c("Aichach-Friedberg, Landkreis", "Alb-Donau-Kreis", 
      "Altmarkkreis Salzwedel", "Alzey-Worms, Landkreis", "Amberg-Sulzbach, Landkreis", 
      "Ammerland, Landkreis", "Anhalt-Bitterfeld, Landkreis", "Ansbach, Landkreis", 
      "Aschaffenburg, Landkreis", "Augsburg, Landkreis", "Aurich, Landkreis", 
      "BÃ¶blingen, Landkreis", "BÃ¶rde, Landkreis", "Bad DÃ¼rkheim, Landkreis", 
      "Bad Kissingen, Landkreis", "Bad Kreuznach, Landkreis", "Bad TÃ¶lz-Wolfratshausen, Landkreis", 
      "Barnim, Landkreis", "Bautzen, Landkreis", "Bayreuth", "Bayreuth, Landkreis", 
      "BergstraÃŸe, Landkreis", "Berlin", "Biberach, Landkreis", 
      "Bodenseekreis", "Borken, Kreis", "Brandenburg an der Havel, Kreisfreie Stadt", 
      "Breisgau-Hochschwarzwald, Landkreis", "Bremen, Kreisfreie Stadt", 
      "Bremerhaven, Kreisfreie Stadt", "Burgenlandkreis", "Calw, Landkreis", 
      "Celle, Landkreis", "Cham, Landkreis", "Chemnitz, Stadt", 
      "Cloppenburg, Landkreis", "Coburg, Landkreis", "Cottbus, Kreisfreie Stadt", 
      "Cuxhaven, Landkreis", "Dachau, Landkreis", "Dahme-Spreewald, Landkreis", 
      "Darmstadt-Dieburg, Landkreis", "Deggendorf, Landkreis", 
      "Dessau-RoÃŸlau, Kreisfreie Stadt", "Diepholz, Landkreis", 
      "Dillingen a.d.Donau, Landkreis", "Dingolfing-Landau, Landkreis", 
      "Dithmarschen, Landkreis", "Donau-Ries, Landkreis", "Donnersbergkreis", 
      "Dresden, Stadt", "Ebersberg, Landkreis", "Eichsfeld, Kreis", 
      "EichstÃ¤tt, Landkreis", "Eisenach, krsfr. Stadt", "Elbe-Elster, Landkreis", 
      "Emmendingen, Landkreis", "Emsland, Landkreis", "Ennepe-Ruhr-Kreis", 
      "Enzkreis", "Erding, Landkreis", "Erfurt, krsfr. Stadt", 
      "Erlangen-HÃ¶chstadt, Landkreis", "Erzgebirgskreis", "Esslingen, Landkreis", 
      "FÃ¼rstenfeldbruck, Landkreis", "FÃ¼rth, Landkreis", "Forchheim, Landkreis", 
      "Frankfurt (Oder), Kreisfreie Stadt", "Frankfurt am Main, Kreisfreie Stadt", 
      "Freising, Landkreis", "Freudenstadt, Landkreis", "Freyung-Grafenau, Landkreis", 
      "Friesland, Landkreis", "Fulda, Landkreis", "GÃ¶ppingen, Landkreis", 
      "GÃ¶rlitz, Landkreis", "GÃ¶ttingen, Landkreis", "Garmisch-Partenkirchen, Landkreis", 
      "GieÃŸen, Landkreis", "Gifhorn, Landkreis", "Goslar, Landkreis", 
      "Gotha, Kreis", "Grafschaft Bentheim, Landkreis", "Greiz, Kreis", 
      "HÃ¶xter, Kreis", "HaÃŸberge, Landkreis", "Halle (Saale), Kreisfreie Stadt", 
      "Hamburg", "Hameln-Pyrmont, Landkreis", "Hamm, Kreisfreie Stadt", 
      "Harburg, Landkreis", "Harz, Landkreis", "Havelland, Landkreis", 
      "Heidekreis, Landkreis", "Heidelberg, Kreisfreie Stadt", 
      "Heidenheim, Landkreis", "Heilbronn, Landkreis", "Heinsberg, Kreis", 
      "Hersfeld-Rotenburg, Landkreis", "Herzogtum Lauenburg, Landkreis", 
      "Hildburghausen, Kreis", "Hildesheim, Landkreis", "Hochsauerlandkreis", 
      "Hochtaunuskreis", "Hof, Landkreis", "Holzminden, Landkreis", 
      "Ilm-Kreis", "Ingolstadt", "Jerichower Land, Landkreis", 
      "KÃ¶ln, Kreisfreie Stadt", "Kaiserslautern, Landkreis", "Karlsruhe, Kreisfreie Stadt", 
      "Karlsruhe, Landkreis", "Kassel, Landkreis", "Kelheim, Landkreis", 
      "Kitzingen, Landkreis", "Kleve, Kreis", "Konstanz, Landkreis", 
      "Kronach, Landkreis", "Kulmbach, Landkreis", "Kusel, Landkreis", 
      "KyffhÃ¤userkreis", "LÃ¶rrach, Landkreis", "LÃ¼chow-Dannenberg, Landkreis", 
      "LÃ¼neburg, Landkreis", "Lahn-Dill-Kreis", "Landkreis Ludwigslust-Parchim", 
      "Landkreis Mecklenburgische Seenplatte", "Landkreis Nordwestmecklenburg", 
      "Landkreis Rostock", "Landkreis Vorpommern-Greifswald", "Landkreis Vorpommern-RÃ¼gen", 
      "Landsberg am Lech, Landkreis", "Landshut, Landkreis", "Leer, Landkreis", 
      "Leipzig, Landkreis", "Lichtenfels, Landkreis", "Limburg-Weilburg, Landkreis", 
      "Lippe, Kreis", "Ludwigsburg, Landkreis", "MÃ¤rkisch-Oderland, Landkreis", 
      "MÃ¤rkischer Kreis", "MÃ¼hldorf a.Inn, Landkreis", "MÃ¼nchen, Landeshauptstadt", 
      "MÃ¼nchen, Landkreis", "Main-Spessart, Landkreis", "Main-Tauber-Kreis", 
      "Main-Taunus-Kreis", "Mainz-Bingen, Landkreis", "Mannheim, UniversitÃ¤tsstadt, Kreisfreie Stadt", 
      "Mansfeld-SÃ¼dharz, Landkreis", "Marburg-Biedenkopf, Landkreis", 
      "Mayen-Koblenz, Landkreis", "MeiÃŸen, Landkreis", "Mettmann, Kreis", 
      "Minden-LÃ¼bbecke, Kreis", "Mittelsachsen, Landkreis", "NÃ¼rnberg", 
      "NÃ¼rnberger Land, Landkreis", "Neckar-Odenwald-Kreis", "Neu-Ulm, Landkreis", 
      "Neuburg-Schrobenhausen, Landkreis", "Neumarkt i.d.OPf., Landkreis", 
      "Neustadt a.d.Aisch-Bad Windsheim, Landkreis", "Neustadt a.d.Waldnaab, Landkreis", 
      "Neustadt an der WeinstraÃŸe, Kreisfreie Stadt", "Neuwied, Landkreis", 
      "Nienburg (Weser), Landkreis", "Nordfriesland, Landkreis", 
      "Nordhausen, Kreis", "Nordsachsen, Landkreis", "Northeim, Landkreis", 
      "OberallgÃ¤u, Landkreis", "Oberhavel, Landkreis", "Oberspreewald-Lausitz, Landkreis", 
      "Odenwaldkreis", "Oder-Spree, Landkreis", "Offenbach, Landkreis", 
      "Oldenburg, Landkreis", "Olpe, Kreis", "Ortenaukreis", "OsnabrÃ¼ck, Landkreis", 
      "Ostalbkreis", "OstallgÃ¤u, Landkreis", "Osterholz, Landkreis", 
      "Osterode am Harz, Landkreis", "Ostholstein, Landkreis", 
      "Ostprignitz-Ruppin, Landkreis", "Passau, Landkreis", "Peine, Landkreis", 
      "Pfaffenhofen a.d.Ilm, Landkreis", "Pinneberg, Landkreis", 
      "PlÃ¶n, Landkreis", "Potsdam-Mittelmark, Landkreis", "Potsdam, Kreisfreie Stadt", 
      "Prignitz, Landkreis", "Rastatt, Landkreis", "Ravensburg, Landkreis", 
      "Regen, Landkreis", "Regensburg, Landkreis", "Region Hannover, Landkreis", 
      "Rems-Murr-Kreis", "Rendsburg-EckernfÃ¶rde, Landkreis", "Reutlingen, Landkreis", 
      "RhÃ¶n-Grabfeld, Landkreis", "Rhein-Kreis Neuss", "Rhein-Neckar-Kreis", 
      "Rhein-Sieg-Kreis", "Rheingau-Taunus-Kreis", "Rheinisch-Bergischer Kreis", 
      "Rosenheim, Landkreis", "Rotenburg (WÃ¼mme), Landkreis", 
      "Roth, Landkreis", "Rottweil, Landkreis", "SÃ¤chsische Schweiz-Osterzgebirge, Landkreis", 
      "SÃ¶mmerda, Kreis", "SÃ¼dliche WeinstraÃŸe, Landkreis", "SÃ¼dwestpfalz, Landkreis", 
      "Saale-Holzland-Kreis", "Saale-Orla-Kreis", "Saalekreis", 
      "Saalfeld-Rudolstadt, Kreis", "Salzlandkreis", "Schaumburg, Landkreis", 
      "Schleswig-Flensburg, Landkreis", "Schmalkalden-Meiningen, Kreis", 
      "Schwabach", "Schwandorf, Landkreis", "Schweinfurt", "Schweinfurt, Landkreis", 
      "Segeberg, Landkreis", "Siegen-Wittgenstein, Kreis", "Sigmaringen, Landkreis", 
      "Soest, Kreis", "Sonneberg, Kreis", "Spree-NeiÃŸe, Landkreis", 
      "Stade, Landkreis", "Starnberg, Landkreis", "Steinburg, Landkreis", 
      "Steinfurt, Kreis", "Stendal, Landkreis", "Stormarn, Landkreis", 
      "Straubing-Bogen, Landkreis", "Stuttgart, Landeshauptstadt, Kreisfreie Stadt", 
      "TÃ¼bingen, Landkreis", "Teltow-FlÃ¤ming, Landkreis", "Traunstein, Landkreis", 
      "Uckermark, Landkreis", "Uelzen, Landkreis", "Unstrut-Hainich-Kreis", 
      "UnterallgÃ¤u, Landkreis", "Vechta, Landkreis", "Verden, Landkreis", 
      "Viersen, Kreis", "Vogelsbergkreis", "WÃ¼rzburg, Landkreis", 
      "Waldeck-Frankenberg, Landkreis", "Wartburgkreis", "WeiÃŸenburg-Gunzenhausen, Landkreis", 
      "Weilheim-Schongau, Landkreis", "Weimar, krsfr. Stadt", "Weimarer Land, Kreis", 
      "Werra-MeiÃŸner-Kreis", "Wesel, Kreis", "Wesermarsch, Landkreis", 
      "Westerwaldkreis", "Wetteraukreis", "Wiesbaden, Landeshauptstadt, Kreisfreie Stadt", 
      "Wittenberg, Landkreis", "Wittmund, Landkreis", "WolfenbÃ¼ttel, Landkreis", 
      "Wuppertal, Kreisfreie Stadt", "Zollernalbkreis", "Zwickau, Landkreis"
      ), class = "factor"), slope_abundance_plot = c(NA_real_, 
      NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_
      ), p_slope_abundance_plot = c(NA_real_, NA_real_, NA_real_, 
      NA_real_, NA_real_, NA_real_, NA_real_)), .Names = c("site", 
  "year", "species", "abundance", "county", "slope_abundance_plot", 
  "p_slope_abundance_plot"), row.names = c(61L, 75L, 76L, 91L, 
  92L, 93L, 134L), class = "data.frame")
  </code></pre>