diff --git a/src/io/bin.cpp b/src/io/bin.cpp
index 2acdd083b9df..a5430c483d3b 100644
--- a/src/io/bin.cpp
+++ b/src/io/bin.cpp
@@ -352,7 +352,7 @@ namespace LightGBM {
     int zero_cnt = static_cast<int>(total_sample_cnt - num_sample_values - na_cnt);
     // find distinct_values first
     std::vector<double> distinct_values;
-    std::vector<int> counts;
+    std::vector<int> counts;  // count of data points for each distinct feature value.
 
     std::stable_sort(values, values + num_sample_values);
 
@@ -389,7 +389,7 @@ namespace LightGBM {
     }
     min_val_ = distinct_values.front();
     max_val_ = distinct_values.back();
-    std::vector<int> cnt_in_bin;
+    std::vector<int> cnt_in_bin;  // count of data points in each bin.
     int num_distinct_values = static_cast<int>(distinct_values.size());
     if (bin_type_ == BinType::NumericalBin) {
       if (missing_type_ == MissingType::Zero) {
@@ -446,12 +446,12 @@ namespace LightGBM {
           Log::Warning("Met categorical feature which contains sparse values. "
                        "Consider renumbering to consecutive integers started from zero");
         }
-        // sort by counts
+        // sort by counts in descending order
         Common::SortForPair<int, int>(&counts_int, &distinct_values_int, 0, true);
         // will ignore the categorical of small counts
         int cut_cnt = static_cast<int>(
             Common::RoundInt((total_sample_cnt - na_cnt) * 0.99f));
-        size_t cur_cat = 0;
+        size_t cur_cat_idx = 0;  // index of current category.
         categorical_2_bin_.clear();
         bin_2_categorical_.clear();
         int used_cnt = 0;
@@ -467,20 +467,20 @@ namespace LightGBM {
         categorical_2_bin_[-1] = 0;
         cnt_in_bin.push_back(0);
         num_bin_ = 1;
-        while (cur_cat < distinct_values_int.size()
+        while (cur_cat_idx < distinct_values_int.size()
                && (used_cnt < cut_cnt || num_bin_ < max_bin)) {
-          if (counts_int[cur_cat] < min_data_in_bin && cur_cat > 1) {
+          if (counts_int[cur_cat_idx] < min_data_in_bin && cur_cat_idx > 1) {
             break;
           }
-          bin_2_categorical_.push_back(distinct_values_int[cur_cat]);
-          categorical_2_bin_[distinct_values_int[cur_cat]] = static_cast<unsigned int>(num_bin_);
-          used_cnt += counts_int[cur_cat];
-          cnt_in_bin.push_back(counts_int[cur_cat]);
+          bin_2_categorical_.push_back(distinct_values_int[cur_cat_idx]);
+          categorical_2_bin_[distinct_values_int[cur_cat_idx]] = static_cast<unsigned int>(num_bin_);
+          used_cnt += counts_int[cur_cat_idx];
+          cnt_in_bin.push_back(counts_int[cur_cat_idx]);
           ++num_bin_;
-          ++cur_cat;
+          ++cur_cat_idx;
         }
         // Use MissingType::None to represent this bin contains all categoricals
-        if (cur_cat == distinct_values_int.size() && na_cnt == 0) {
+        if (cur_cat_idx == distinct_values_int.size() && na_cnt == 0) {
           missing_type_ = MissingType::None;
         } else {
           missing_type_ = MissingType::NaN;