proof reading: self study data analysis task 1

Author: liamjberrisford

individual_modules/introduction_to_python/analysis_task_1.ipynb

@@ -99,7 +99,7 @@
    "id": "4a28ab32-78b5-48bb-a962-c01f9ad3eaa2",
    "metadata": {},
    "source": [
-    "The expression `np.loadtxt(...)` is a function call that asks Python to run the function `loadtxt` which belongs to the `numpy` library. The dot notation in Python is used most of all as an object attribute/property specifier or for invoking its method. `object.property` will give you the object.property value, `object_name.method()` will invoke on object_name method.\n",
+    "The expression `np.loadtxt(...)` is a function call that asks Python to run the function `loadtxt` which belongs to the `numpy` library. The dot notation in Python is used most of all as an object attribute/property specifier, or for invoking its method. `object.property` will give you the object.property value, `object_name.method()` will invoke on object_name method.\n",
     "\n",
     "As an example, John Smith is the John that belongs to the Smith family. We could use the dot notation to write his name `smith.john`, just as `loadtxt` is a function that belongs to the `numpy` library.\n",
     "\n",
@@ -257,7 +257,7 @@
    "source": [
     "The output tells us that the `data` array variable contains 60 rows and 40 columns. When we created the variable `data` to store our arthritis data, we did not only create the array; we also created information about the array, called members or attributes. This extra information describes `data` in the same way an adjective describes a noun. `data.shape` is an attribute of `data` which describes the dimensions of `data`. We use the same dotted notation for the attributes of variables that we use for the functions in libraries because they have the same part-and-whole relationship.\n",
     "\n",
-    "If we want to get a single number from the array, we must provide an index in square brackets after the variable name, just as we do in math when referring to an element of a matrix.  Our inflammation data has two dimensions, so we will need to use two indices to refer to one specific value:"
+    "If we want to get a single number from the array, we must provide an index in square brackets after the variable name, just as we do in maths when referring to an element of a matrix.  Our inflammation data has two dimensions, so we will need to use two indices to refer to one specific value:"
    ]
   },
   {
@@ -355,7 +355,7 @@
    "id": "6fe8654d-647b-45b0-8f9e-a5ed2061dfd7",
    "metadata": {},
    "source": [
-    "The slice `0:4` means, \"Start at index 0 and go up to, but not including, index 4\". Again, the up-to-but-not including takes a bit of getting used to, but the rule is that the difference between the upper and lower bounds is the number of values in the slice.\n",
+    "The slice `0:4` means, \"Start at index 0 and go up to, but not including, index 4\". Again, the up-to-but-not-including takes a bit of getting used to, but the rule is that the difference between the upper and lower bounds is the number of values in the slice.\n",
     "\n",
     "We don't have to start slices at 0:"
    ]
@@ -455,7 +455,7 @@
     "\n",
     "## Not All Functions Have Input\n",
     "\n",
-    "Generally, a function uses inputs to produce outputs.However, some functions produce outputs without\n",
+    "Generally, a function uses inputs to produce outputs. However, some functions produce outputs without\n",
     "needing any input. For example, checking the current time doesn't require any input."
    ]
   },
@@ -808,7 +808,7 @@
    "metadata": {},
    "source": [
     "## Thin Slices\n",
-    "The expression `element[3:3]` produces an empty string, i.e., a string that contains no characters. If `data` holds our array of patient data, what does `data[3:3, 4:4]` produce?What about `data[3:3, :]`?"
+    "The expression `element[3:3]` produces an empty string, i.e., a string that contains no characters. If `data` holds our array of patient data, what does `data[3:3, 4:4]` produce? What about `data[3:3, :]`?"
    ]
   },
   {
@@ -955,7 +955,7 @@
    "id": "72bcfd3a-bf13-4a28-b161-b84fe58ddd4c",
    "metadata": {},
    "source": [
-    "alling `np.diff(patient3_week1)` would do the following calculations and return the 6 difference values in a new array."
+    "Calling `np.diff(patient3_week1)` would do the following calculations and return the 6 difference values in a new array."
    ]
   },
   {
@@ -1104,7 +1104,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,