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   "source": [
    "## Exercise 1 - Pandas part 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note**: Throughout the exercise, the original data frame is to be processed!"
   ]
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   "cell_type": "markdown",
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   "source": [
    " 1 Add the required libraries and read the file named `testdata.csv` into the DataFrame object."
   ]
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
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   "cell_type": "markdown",
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   "source": [
    " 2 Print the last five rows of the DataFrame object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
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   "source": [
    "3 Print the headers of the data columns as a list object."
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "4 Print the length of `column2` (the number of elements in the column)."
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "5 Print the information of the first row of data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6 Drop the column named `Unnamed: 0` from the data and verify the result in the way you choose."
   ]
  },
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   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
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   "source": [
    "7 Delete rows if the value 0.2 or less appears in the column `column1`."
   ]
  },
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   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8 Print the minimum and maximum value of column `column1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "9 Make the value of the first column of the first row to be `NaN`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10 Save the final result in a file called `data_export.csv` (the file will be used in the next exercise)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#"
   ]
  }
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