diff --git a/hone/hone.py b/hone/hone.py
index 47cf053..9b1ae03 100644
--- a/hone/hone.py
+++ b/hone/hone.py
@@ -1,173 +1,187 @@
-from hone.utils import csv_utils
-import copy
-
-class Hone:
-    def __init__(self):
-        self.delimit_chars = [",", "_", " "]
-        self.csv_filepath = None
-        self.csv = csv_utils.CSVUtils(self.csv_filepath)
-    '''
-    Perform CSV to nested JSON conversion and return resulting JSON.
-    '''
-    def convert(self, csv_filepath):
-        self.set_csv_filepath(csv_filepath)
-        column_names = self.csv.get_column_names()
-        data = self.csv.get_data_rows()
-        column_schema = self.generate_full_structure(column_names)
-        json_struct = self.populate_structure_with_data(column_schema, column_names, data)
-        return json_struct
-    '''
-    Returns dictionary with given data rows fitted to given structure.
-    '''
-
-    def populate_structure_with_data(self, structure, column_names, data_rows):
-        json_struct = []
-        num_columns = len(column_names)
-        mapping = self.get_leaves(structure)
-        for row in data_rows:
-            json_row = copy.deepcopy(structure)
-            i = 0
-            while i < num_columns:
-                cell = row[i]
-                column_name = column_names[i]
-                key_path = mapping[column_name]
-                exec("json_row"+key_path+"="+"'"+cell+"'")
-                i += 1
-            json_struct.append(json_row)
-        return json_struct
-
-    '''
-    Get generated JSON schema.
-    '''
-
-    def get_schema(self, csv_filepath):
-        self.set_csv_filepath(csv_filepath)
-        column_names = self.csv.get_column_names()
-        data = self.csv.get_data_rows()
-        column_struct = self.generate_full_structure(column_names)
-        return column_struct
-
-    '''
-    Generate recursively-nested JSON structure from column_names.
-    '''
-
-    def generate_full_structure(self, column_names):
-        visited = set()
-        structure = {}
-        sorted(column_names)
-        column_names = column_names[::-1]
-        for c1 in column_names:
-            if c1 in visited:
-                continue
-            splits = self.get_valid_splits(c1)
-            for split in splits:
-                nodes = {split: {}}
-                if split in column_names:
-                    continue
-                for c2 in column_names:
-                    if c2 not in visited and self.is_valid_prefix(split, c2):
-                        nodes[split][self.get_split_suffix(split, c2)] = c2
-                if len(nodes[split].keys()) > 1:
-                    structure[split] = self.get_nested_structure(nodes[split])
-                    for val in nodes[split].values():
-                        visited.add(val)
-            if c1 not in visited:  # if column_name not nestable
-                structure[c1] = c1
-        return structure
-
-    '''
-    Generate nested JSON structure given parent structure generated from initial call to get_full_structure
-    '''
-
-    def get_nested_structure(self, parent_structure):
-        column_names = list(parent_structure.keys())
-        visited = set()
-        structure = {}
-        sorted(column_names, reverse=True)
-        for c1 in column_names:
-            if c1 in visited:
-                continue
-            splits = self.get_valid_splits(c1)
-            for split in splits:
-                nodes = {split: {}}
-                if split in column_names:
-                    continue
-                for c2 in column_names:
-                    if c2 not in visited and self.is_valid_prefix(split, c2):
-                        nodes[split][self.get_split_suffix(split, c2)] = parent_structure[c2]
-                        visited.add(c2)
-                if len(nodes[split].keys()) > 1:
-                    structure[split] = self.get_nested_structure(nodes[split])
-            if c1 not in visited:  # if column_name not nestable
-                structure[c1] = parent_structure[c1]
-        return structure
-
-    '''
-    Get the leaf nodes of a nested structure and the path to those nodes.
-    Ex: {"a":{"b":"c"}} => {"c":"['a']['b']"}
-    '''
-
-    def get_leaves(self, structure, path="", result={}):
-        for key, value in structure.items():
-            if type(value) is dict:
-                self.get_leaves(value, path+"['"+key+"']", result)
-            else:
-                result[value] = path+"['"+key+"']"
-        return result
-
-    '''
-    Returns all valid splits for a given column name in descending order by length
-    '''
-
-    def get_valid_splits(self, column_name):
-        splits = []
-        i = len(column_name) - 1
-        while i >= 0:
-            c = column_name[i]
-            if c in self.delimit_chars:
-                split = self.clean_split(column_name[0:i])
-                splits.append(split)
-            i -= 1
-        return sorted(list(set(splits)))
-
-    '''
-    Returns string after split without delimiting characters.
-    '''
-
-    def get_split_suffix(self, split, column_name=""):
-        suffix = column_name[len(split) + 1:]
-        i = 0
-        while i < len(suffix):
-            c = suffix[i]
-            if c not in self.delimit_chars:
-                return suffix[i:]
-            i += 1
-        return suffix
-
-    '''
-    Returns split with no trailing delimiting characters.
-    '''
-
-    def clean_split(self, split):
-        i = len(split) - 1
-        while i >= 0:
-            c = split[i]
-            if c not in self.delimit_chars:
-                return split[0:i + 1]
-            i -= 1
-        return split
-
-    '''
-    Returns true if str_a is a valid prefix of str_b
-    '''
-
-    def is_valid_prefix(self, prefix, base):
-        if base.startswith(prefix):
-            if base[len(prefix)] in self.delimit_chars:
-                return True
-        return False
-
-    def set_csv_filepath(self, csv_filepath):
-        self.csv_filepath = csv_filepath
-        self.csv.filepath = self.csv_filepath
-
+from hone.utils import csv_utils
+import copy
+
+class Hone:
+    def __init__(self):
+        self.delimit_chars = [",", "_", " "]
+        self.csv_filepath = None
+        self.csv = csv_utils.CSVUtils(self.csv_filepath)
+    '''
+    Perform CSV to nested JSON conversion and return resulting JSON.
+    '''
+    def convert(self, csv_filepath):
+        self.set_csv_filepath(csv_filepath)
+        column_names = self.csv.get_column_names()
+        data = self.csv.get_data_rows()
+        cell_type = self.csv.data_type_check(data,column_names)
+        column_schema = self.generate_full_structure(column_names)
+        # change
+        json_struct = self.populate_structure_with_data(column_schema, column_names, data, cell_type)
+        # was json_struct = self.populate_structure_with_data(column_schema, column_names, data)
+        return json_struct
+    '''
+    Returns dictionary with given data rows fitted to given structure.
+    '''
+
+    def populate_structure_with_data(self, structure, column_names, data_rows, cell_type):
+        # change ..added cell_type..
+        json_struct = []
+        num_columns = len(column_names)
+        mapping = self.get_leaves(structure)
+        row = 0
+        while row < len(data_rows):
+        # change - was ...for row in data_rows:...
+            json_row = copy.deepcopy(structure)
+            col = 0
+            # changed i to col
+            while col < len(column_names):
+                column_name = column_names[col]
+                key_path = mapping[column_name]
+                # Changes
+                if cell_type[row][col] == 'string':
+                    exec("json_row"+key_path+"="+"'"+data_rows[row][col]+"'")
+                else:
+                    exec("json_row"+key_path+"="+data_rows[row][col])
+                col += 1
+            json_struct.append(json_row)
+            row +=1
+            
+        return json_struct
+
+    '''
+    Get generated JSON schema.
+    '''
+
+    def get_schema(self, csv_filepath):
+        self.set_csv_filepath(csv_filepath)
+        column_names = self.csv.get_column_names()
+        data = self.csv.get_data_rows()
+        column_struct = self.generate_full_structure(column_names)
+        return column_struct
+
+    '''
+    Generate recursively-nested JSON structure from column_names.
+    '''
+
+    def generate_full_structure(self, column_names):
+        visited = set()
+        structure = {}
+        sorted(column_names)
+        column_names = column_names[::-1]
+        for c1 in column_names:
+            if c1 in visited:
+                continue
+            splits = self.get_valid_splits(c1)
+            for split in splits:
+                nodes = {split: {}}
+                if split in column_names:
+                    continue
+                for c2 in column_names:
+                    #print(c1,c2)
+                    if c2 not in visited and self.is_valid_prefix(split, c2):
+                        nodes[split][self.get_split_suffix(split, c2)] = c2
+                if len(nodes[split].keys()) > 1:
+                    structure[split] = self.get_nested_structure(nodes[split])
+                    for val in nodes[split].values():
+                        visited.add(val)
+            if c1 not in visited:  # if column_name not nestable
+                structure[c1] = c1
+        return structure
+
+    '''
+    Generate nested JSON structure given parent structure generated from initial call to get_full_structure
+    '''
+
+    def get_nested_structure(self, parent_structure):
+        column_names = list(parent_structure.keys())
+        visited = set()
+        structure = {}
+        sorted(column_names, reverse=True)
+        for c1 in column_names:
+            if c1 in visited:
+                continue
+            splits = self.get_valid_splits(c1)
+            for split in splits:
+                nodes = {split: {}}
+                if split in column_names:
+                    continue
+                for c2 in column_names:
+                    if c2 not in visited and self.is_valid_prefix(split, c2):
+                        nodes[split][self.get_split_suffix(split, c2)] = parent_structure[c2]
+                        visited.add(c2)
+                if len(nodes[split].keys()) > 1:
+                    structure[split] = self.get_nested_structure(nodes[split])
+            if c1 not in visited:  # if column_name not nestable
+                structure[c1] = parent_structure[c1]
+        return structure
+
+    '''
+    Get the leaf nodes of a nested structure and the path to those nodes.
+    Ex: {"a":{"b":"c"}} => {"c":"['a']['b']"}
+    '''
+
+    def get_leaves(self, structure, path="", result={}):
+        for key, value in structure.items():
+            if type(value) is dict:
+                self.get_leaves(value, path+"['"+key+"']", result)
+            else:
+                result[value] = path+"['"+key+"']"
+    
+        return result
+
+    '''
+    Returns all valid splits for a given column name in descending order by length
+    '''
+
+    def get_valid_splits(self, column_name):
+        splits = []
+        i = len(column_name) - 1
+        while i >= 0:
+            c = column_name[i]
+            if c in self.delimit_chars:
+                split = self.clean_split(column_name[0:i])
+                splits.append(split)
+            i -= 1
+        return sorted(list(set(splits)))
+
+    '''
+    Returns string after split without delimiting characters.
+    '''
+
+    def get_split_suffix(self, split, column_name=""):
+        suffix = column_name[len(split) + 1:]
+        i = 0
+        while i < len(suffix):
+            c = suffix[i]
+            if c not in self.delimit_chars:
+                return suffix[i:]
+            i += 1
+        return suffix
+
+    '''
+    Returns split with no trailing delimiting characters.
+    '''
+
+    def clean_split(self, split):
+        i = len(split) - 1
+        while i >= 0:
+            c = split[i]
+            if c not in self.delimit_chars:
+                return split[0:i + 1]
+            i -= 1
+        return split
+
+    '''
+    Returns true if str_a is a valid prefix of str_b
+    '''
+
+    def is_valid_prefix(self, prefix, base):
+        if base.startswith(prefix):
+            if base[len(prefix)] in self.delimit_chars:
+                return True
+        return False
+
+    def set_csv_filepath(self, csv_filepath):
+        self.csv_filepath = csv_filepath
+        self.csv.filepath = self.csv_filepath
+
diff --git a/hone/utils/csv_utils.py b/hone/utils/csv_utils.py
index 34203b8..4db71e2 100644
--- a/hone/utils/csv_utils.py
+++ b/hone/utils/csv_utils.py
@@ -1,65 +1,93 @@
-"""
-Simple methods for processing CSV files
-"""
-
-from contextlib import contextmanager
-
-class CSVUtils:
-    def __init__(self, csv_filepath):
-        self.filepath = csv_filepath
-
-    # Parses and returns first row of CSV (column names)
-    def get_column_names(self):
-        with self.open_csv() as f:
-            cols = self.parse_row(f.readline())
-        return cols
-
-    # Returns parsed rows of CSV (excluding column names)
-    def get_data_rows(self):
-        data_rows = []
-        with self.open_csv() as f:
-            f.readline()  # discard column names
-            while True:
-                row = f.readline()
-                if row != '':
-                    data_rows.append(self.parse_row(row))
-                else:
-                    break
-        return data_rows
-
-    # Open CSV in given mode (default is read mode)
-    @contextmanager
-    def open_csv(self, mode='r'):
-        f = open(self.filepath, mode, encoding='utf-8-sig')
-        try:
-            yield f
-        finally:
-            f.close()
-
-    # Parse given row (list of cells)
-    @staticmethod
-    def parse_row(row):
-        row = row[:-1]
-        cells = []
-
-        quote_flag = False
-        split_index = 0
-        i = 0
-
-        # parse rows
-        while i < len(row):
-            c = row[i]
-            if c == '"':
-                quote_flag = not quote_flag
-            elif c == ',':
-                if not quote_flag:
-                    cells.append(row[split_index:i])
-                    split_index = i+1
-            i += 1
-
-        # add last cell in row
-        if split_index != len(row):
-            cells.append(row[split_index:])
-
-        cells = [cell.strip(' "') for cell in cells]
-        return cells
+"""
+Simple methods for processing CSV files
+"""
+
+from contextlib import contextmanager
+import re
+
+class CSVUtils:
+    def __init__(self, csv_filepath):
+        self.filepath = csv_filepath
+
+    # Parses and returns first row of CSV (column names)
+    def get_column_names(self):
+        with self.open_csv() as f:
+            cols = self.parse_row(f.readline())
+        return cols
+
+    # Returns parsed rows of CSV (excluding column names)
+    def get_data_rows(self):
+        data_rows = []
+        with self.open_csv() as f:
+            f.readline()  # discard column names
+            while True:
+                row = f.readline()
+                if row != '':
+                    data_rows.append(self.parse_row(row))
+                else:
+                    break
+        return data_rows
+
+    def data_type_check(self, cell_data,column_names):
+        # return data type, only checks for accountID, integer or string, boolean could be added
+        accountid = re.compile("^[0-9]{12}$")
+        number = re.compile("^\d+$")
+        row = 0
+        col = 0
+        cell_type = []
+        inner_array = []
+
+        while row < len(cell_data):
+            while col < (len(column_names)):
+                if accountid.match(cell_data[row][col]):
+                    inner_array.append('string')
+                else:
+                    if number.match(cell_data[row][col]):
+                        inner_array.append('integer')
+                    else:
+                        inner_array.append('string')
+                col += 1
+            cell_type.append(inner_array)
+            row += 1
+        
+        #print(cell_type)
+        return cell_type
+
+    # Open CSV in given mode (default is read mode)
+    @contextmanager
+    def open_csv(self, mode='r'):
+        f = open(self.filepath, mode, encoding='utf-8-sig')
+        try:
+            yield f
+        finally:
+            f.close()
+
+    # Parse given row (list of cells)
+    @staticmethod
+    def parse_row(row):
+        row = row[:-1]
+        cells = []
+
+        quote_flag = False
+        split_index = 0
+        i = 0
+
+        # parse rows
+        while i < len(row):
+            
+            c = row[i]
+
+            if c == '"':
+                quote_flag = not quote_flag
+            elif c == ',':
+                if not quote_flag:
+                    cells.append(row[split_index:i])
+                    split_index = i+1
+            i += 1
+
+        # add last cell in row
+        if split_index != len(row):
+            cells.append(row[split_index:])
+
+        cells = [cell.strip(' "') for cell in cells]
+        return cells