fixed tiny formatting issues in lesson 5 pandas notebooks

Author: VuokkoH

notebooks/L5/Pandas/Exploring-data-using-pandas.ipynb

@@ -24,8 +24,9 @@
     "1. Start a jupyter lab instance (using the links at the top of this page) and open this lesson in an interactive mode.\n",
     "2. Have a look at the input data which is a text file containing weather observations from Kumpula\n",
     "\n",
-    "    - The data file name is [Kumpula-June-2016-w-metadata.txt](Kumpula-June-2016-w-metadata.txt)\n",
+    "    - The data file name is `Kumpula-June-2016-w-metadata.txt`\n",
     "    - The file is available in the binder and CSC notebook instances, under L5 folder \n",
+    "    - or, you can download the file from [here](https://github.com/geo-python/notebooks/blob/master/notebooks/L5/Kumpula-June-2016-w-metadata.txt)\n",
     "    - The data file contains observed daily mean, minimum, and maximum temperatures from June 2016 recorded from the Kumpula weather observation station in Helsinki.\n",
     "    - The data has been derived from a data file of daily temperature measurments downloaded from the [US National Oceanographic and Atmospheric Administration's National Centers for Environmental Information climate database](https://www.ncdc.noaa.gov/cdo-web/).\n",
     "    - There are something like 30 lines of data in the data file.\n",
@@ -562,7 +563,7 @@
    },
    "outputs": [],
    "source": [
-    "# Create Pandas Series from the list\n",
+    "# Create Pandas Series from a list\n",
     "myList = [1, 2, 3, 4, 5, 6, 7.0]\n"
    ]
   },
@@ -575,7 +576,7 @@
    "source": [
     "As you can see, ``myList`` is converted to a Pandas Series using the ``ps.Series()`` function. Also, note that Pandas is smart about the conversion, detecting a single floating point value (``7.0``) and assigning all values in the Series the data type float64.\n",
     "\n",
-    "In turn, we could convert this series back into a pandas dataframe by calling the [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html) -function:"
+    "In turn, we could convert this series back into a pandas dataframe by initiating a new [pandas.DataFrame](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html):"
    ]
   },
   {

notebooks/L5/Pandas/processing-data-with-pandas.ipynb

@@ -654,7 +654,7 @@
    },
    "outputs": [],
    "source": [
-    "# Number of unique values\n"
+    "# unique values as list\n"
    ]
   },
   {
@@ -676,7 +676,9 @@
     "editable": true
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "# Number of unique values"
+   ]
   },
   {
    "cell_type": "markdown",