diff --git a/.gitignore b/.gitignore
index 167d464..e342915 100644
--- a/.gitignore
+++ b/.gitignore
@@ -27,3 +27,6 @@ venv/
 
 # vim config
 .vim/
+
+*.ods
+.py39/
diff --git a/pandas_ods_reader/algo.py b/pandas_ods_reader/algo.py
index 8c872cf..6d391a9 100644
--- a/pandas_ods_reader/algo.py
+++ b/pandas_ods_reader/algo.py
@@ -1,13 +1,21 @@
 from collections import OrderedDict
+from unittest import skip
 
 import pandas as pd
 
 from .utils import sanitize_df
 
 
-def parse_data(backend, rows, headers=True, columns=None):
+def parse_data(backend, rows, headers=True, columns=None, skiprows=None):
     df_dict = OrderedDict()
     col_index = {}
+    if skiprows is not None:
+        if isinstance(skiprows, int):
+            for _ in range(skiprows):
+                next(rows)
+        else:
+            message = f"'skiprows' must be int. {type(skiprows)} was given."
+            raise ValueError(message)
     for i, row in enumerate(rows):
         # row is a list of cells
         if headers and i == 0 and not columns:
@@ -59,8 +67,13 @@ def parse_data(backend, rows, headers=True, columns=None):
     return df
 
 
-def read_data(backend, file_or_path, sheet_id, headers=True, columns=None):
+def read_data(
+    backend, file_or_path, sheet_id,
+    headers=True, columns=None, skiprows=0
+):
     doc = backend.get_doc(file_or_path)
     rows = backend.get_rows(doc, sheet_id)
-    df = parse_data(backend, rows, headers=headers, columns=columns)
+    df = parse_data(
+        backend, rows, headers=headers, columns=columns, skiprows=skiprows
+    )
     return sanitize_df(df)
diff --git a/pandas_ods_reader/main.py b/pandas_ods_reader/main.py
index bd8caa0..8de5548 100644
--- a/pandas_ods_reader/main.py
+++ b/pandas_ods_reader/main.py
@@ -8,7 +8,7 @@ from . import algo
 EXT_MAP = {".ods": ods, ".fods": fods}
 
 
-def read_ods(file_or_path, sheet=1, headers=True, columns=None):
+def read_ods(file_or_path, sheet=1, headers=True, columns=None, skiprows=0):
     """
     Read in the provided ods or .ods file and convert it to `pandas.DataFrame`.
     Will detect the filetype based on the file's extension or fall back to
@@ -33,5 +33,8 @@ def read_ods(file_or_path, sheet=1, headers=True, columns=None):
     """
     backend = EXT_MAP.get(Path(file_or_path).suffix, ods)
     return algo.read_data(
-        backend, file_or_path, sheet, headers=headers, columns=columns
+        backend,
+        file_or_path,
+        sheet,
+        headers=headers, columns=columns, skiprows=skiprows
     )
diff --git a/test.ipynb b/test.ipynb
new file mode 100644
index 0000000..0c02ddb
--- /dev/null
+++ b/test.ipynb
@@ -0,0 +1,176 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pandas_ods_reader import read_ods"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file_path = \"Dicionário_Microdados_Enem_2021.ods\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>column.0</th>\n",
+       "      <th>column.1</th>\n",
+       "      <th>column.2</th>\n",
+       "      <th>column.3</th>\n",
+       "      <th>column.4</th>\n",
+       "      <th>column.5</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>NU_INSCRICAO</td>\n",
+       "      <td>Número de inscrição1</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>Numérica</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>NU_ANO</td>\n",
+       "      <td>Ano do Enem</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>Numérica</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>TP_FAIXA_ETARIA</td>\n",
+       "      <td>Faixa etária2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Menor de 17 anos</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>Numérica</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>2</td>\n",
+       "      <td>17 anos</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>3</td>\n",
+       "      <td>18 anos</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>None</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          column.0               column.1 column.2          column.3  \\\n",
+       "0     NU_INSCRICAO  Número de inscrição1      None              None   \n",
+       "1           NU_ANO            Ano do Enem     None              None   \n",
+       "2  TP_FAIXA_ETARIA          Faixa etária2        1  Menor de 17 anos   \n",
+       "3             None                   None        2           17 anos   \n",
+       "4             None                   None        3           18 anos   \n",
+       "\n",
+       "   column.4  column.5  \n",
+       "0      12.0  Numérica  \n",
+       "1       4.0  Numérica  \n",
+       "2       2.0  Numérica  \n",
+       "3       NaN      None  \n",
+       "4       NaN      None  "
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = read_ods(file_path, headers=False, skiprows=5)\n",
+    "data.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.14 ('.py39': venv)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.14"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "6ea8410887842cf63ab95c5e43eca8b07627ccf142be6aa1d4d3a20bcd58cd50"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}