diff --git a/danfojs-browser/src/core/frame.js b/danfojs-browser/src/core/frame.js
index 10636107..8f8dd18e 100644
--- a/danfojs-browser/src/core/frame.js
+++ b/danfojs-browser/src/core/frame.js
@@ -2071,6 +2071,7 @@ export class DataFrame extends Ndframe {
     col_vals.forEach((col, i) => {
       // self[col_names[i]] = new Series(col, { columns: col_names[i], index: self.index })
       Object.defineProperty(self, col_names[i], {
+        configurable: true,
         get() {
           return new Series(col, { columns: col_names[i], index: self.index });
         },
diff --git a/danfojs-node/src/core/frame.js b/danfojs-node/src/core/frame.js
index a5ff8820..f92f23b1 100644
--- a/danfojs-node/src/core/frame.js
+++ b/danfojs-node/src/core/frame.js
@@ -597,32 +597,32 @@ export class DataFrame extends Ndframe {
         for (let j = 1; j < value.length; j++) {
           let curr_val = value[j];
           switch (ops) {
-            case "max":
-              if (curr_val > temp_val) {
-                temp_val = curr_val;
-                temp_data.push(curr_val);
-              } else {
-                temp_data.push(temp_val);
-              }
-              break;
-            case "min":
-              if (curr_val < temp_val) {
-                temp_val = curr_val;
-                temp_data.push(curr_val);
-              } else {
-                temp_data.push(temp_val);
-              }
-              break;
-            case "sum":
-              temp_val = temp_val + curr_val;
+          case "max":
+            if (curr_val > temp_val) {
+              temp_val = curr_val;
+              temp_data.push(curr_val);
+            } else {
               temp_data.push(temp_val);
-
-              break;
-            case "prod":
-              temp_val = temp_val * curr_val;
+            }
+            break;
+          case "min":
+            if (curr_val < temp_val) {
+              temp_val = curr_val;
+              temp_data.push(curr_val);
+            } else {
               temp_data.push(temp_val);
+            }
+            break;
+          case "sum":
+            temp_val = temp_val + curr_val;
+            temp_data.push(temp_val);
+
+            break;
+          case "prod":
+            temp_val = temp_val * curr_val;
+            temp_data.push(temp_val);
 
-              break;
+            break;
           }
         }
         data.push(temp_data);
@@ -1657,24 +1657,24 @@ export class DataFrame extends Ndframe {
     }
 
     switch (logical_type) {
-      case "lt":
-        int_vals = tf.tensor(this.values).less(other).arraySync();
-        break;
-      case "gt":
-        int_vals = tf.tensor(this.values).greater(other).arraySync();
-        break;
-      case "le":
-        int_vals = tf.tensor(this.values).lessEqual(other).arraySync();
-        break;
-      case "ge":
-        int_vals = tf.tensor(this.values).greaterEqual(other).arraySync();
-        break;
-      case "ne":
-        int_vals = tf.tensor(this.values).notEqual(other).arraySync();
-        break;
-      case "eq":
-        int_vals = tf.tensor(this.values).equal(other).arraySync();
-        break;
+    case "lt":
+      int_vals = tf.tensor(this.values).less(other).arraySync();
+      break;
+    case "gt":
+      int_vals = tf.tensor(this.values).greater(other).arraySync();
+      break;
+    case "le":
+      int_vals = tf.tensor(this.values).lessEqual(other).arraySync();
+      break;
+    case "ge":
+      int_vals = tf.tensor(this.values).greaterEqual(other).arraySync();
+      break;
+    case "ne":
+      int_vals = tf.tensor(this.values).notEqual(other).arraySync();
+      break;
+    case "eq":
+      int_vals = tf.tensor(this.values).equal(other).arraySync();
+      break;
     }
     let bool_vals = utils.__map_int_to_bool(int_vals, 2);
     let df = new DataFrame(bool_vals, {
@@ -1846,27 +1846,27 @@ export class DataFrame extends Ndframe {
     let temp_col = col_values[col_idx];
 
     switch (kwargs["dtype"]) {
-      case "float32":
-        temp_col.map((val) => {
-          new_col_values.push(Number(val));
-        });
-        col_values[col_idx] = new_col_values;
-        break;
-      case "int32":
-        temp_col.map((val) => {
-          new_col_values.push(Number(Number(val).toFixed()));
-        });
-        col_values[col_idx] = new_col_values;
+    case "float32":
+      temp_col.map((val) => {
+        new_col_values.push(Number(val));
+      });
+      col_values[col_idx] = new_col_values;
+      break;
+    case "int32":
+      temp_col.map((val) => {
+        new_col_values.push(Number(Number(val).toFixed()));
+      });
+      col_values[col_idx] = new_col_values;
 
-        break;
-      case "string":
-        temp_col.map((val) => {
-          new_col_values.push(String(val));
-        });
-        col_values[col_idx] = new_col_values;
-        break;
-      default:
-        break;
+      break;
+    case "string":
+      temp_col.map((val) => {
+        new_col_values.push(String(val));
+      });
+      col_values[col_idx] = new_col_values;
+      break;
+    default:
+      break;
     }
 
     let new_col_obj = {};
@@ -2074,6 +2074,7 @@ export class DataFrame extends Ndframe {
     col_vals.forEach((col, i) => {
       // self[col_names[i]] = new Series(col, { columns: col_names[i], index: self.index })
       Object.defineProperty(self, col_names[i], {
+        configurable: true,
         get() {
           return new Series(col, { columns: col_names[i], index: self.index });
         },