Update...

Update f22/andy_lec_notes/lec19_Oct21_JSON/.ipynb_checkpoints/lec19_json_template-checkpoint.ipynb, f22/andy_lec_notes/lec19_Oct21_JSON/.ipynb_checkpoints/lec_19_850-checkpoint.ipynb, f22/andy_lec_notes/lec19_Oct21_JSON/cs220_survey_data.csv, f22/andy_lec_notes/lec19_Oct21_JSON/kiva.json, f22/andy_lec_notes/lec19_Oct21_JSON/kiva_query.txt, f22/andy_lec_notes/lec19_Oct21_JSON/lec19_json_completed.ipynb, f22/andy_lec_notes/lec19_Oct21_JSON/lec19_json_template.ipynb, f22/andy_lec_notes/lec19_Oct21_JSON/lec19_worksheet_answers.ipynb, f22/andy_lec_notes/lec19_Oct21_JSON/readme.md, f22/andy_lec_notes/lec19_Oct21_JSON/score_history.json

Update...
2d62714a · Andy Kuemmel · ba33462f · 2d62714a · 2d62714a · 2d62714a
Commit 2d62714a authored 2 years ago by Andy Kuemmel
--- a/f22/andy_lec_notes/lec_19/.ipynb_checkpoints/lec19_json_template-checkpoint.ipynb
+++ b/f22/andy_lec_notes/lec_19/.ipynb_checkpoints/lec19_json_template-checkpoint.ipynb
--- a/f22/andy_lec_notes/lec_19/.ipynb_checkpoints/lec_19_850-checkpoint.ipynb
+++ b/f22/andy_lec_notes/lec_19/.ipynb_checkpoints/lec_19_850-checkpoint.ipynb
--- a/f22/andy_lec_notes/lec_19/cs220_survey_data.csv
+++ b/f22/andy_lec_notes/lec_19/cs220_survey_data.csv
--- a/f22/andy_lec_notes/lec_19/kiva.json
+++ b/f22/andy_lec_notes/lec_19/kiva.json
--- a/f22/andy_lec_notes/lec_19/kiva_query.txt
+++ b/f22/andy_lec_notes/lec_19/kiva_query.txt
--- a/f22/andy_lec_notes/lec_19/lec19_json_850.ipynb
+++ b/f22/andy_lec_notes/lec_19/lec19_json_850.ipynb
--- a/f22/andy_lec_notes/lec_19/lec19_json_template.ipynb
+++ b/f22/andy_lec_notes/lec_19/lec19_json_template.ipynb
@@ -205,7 +205,7 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "## March 11:  JSON Files\n",
+    "## Lecture 19:  JSON Files\n",
    "Learning Objectives:\n",
    "- Interpret JSON formatted data and recognize differences between JSON and Python\n",
    "- Deserialize data from JSON for use in Python programs (read)\n",

 %% Cell type:code id: tags:
 ``` python
 import csv
 import json # today's topic!
 ```
 %% Cell type:code id: tags:
 ``` python
 # Warmup 0: Recall how to read in the csv data
 # source:  Automate the Boring Stuff with Python
 def process_csv(filename):
    exampleFile = open(filename, encoding="utf-8")
    exampleReader = csv.reader(exampleFile)
    exampleData = list(exampleReader)
    exampleFile.close()
    return exampleData
 survey_data = process_csv('cs220_survey_data.csv')
 header = None
 header
 ```
 %% Cell type:code id: tags:
 ``` python
 # Warmup 1: Complete the cell function
 def cell(row_idx, col_name):
    col_idx = None
    val = None
    if val == "":
        return None
    elif col_name in ["Age"]:  # used 'in' to allow for easy modification
        return int(val)
    else:
        return val
 cell(3, 'Pizza topping')
 ```
 %% Cell type:code id: tags:
 ``` python
 # Warmup 2: put survey_data into buckets by lecture
 # make a dictionary of lists
 # key is the lecture
 rows = survey_data[1:]
 lecture_dict = {}
 for i in range(len(rows)):
    lecture = cell(i, 'Lecture')
    # what goes here?
 lecture_dict
 ```
 %% Output
    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    <ipython-input-5-5bd8c0d3ae8b> in <module>
          3 # key is the lecture
          4
    ----> 5 rows = survey_data[1:]
          6
          7 lecture_dict = {}
    NameError: name 'survey_data' is not defined
 %% Cell type:code id: tags:
 ``` python
 # Warmup 3:  In lecture_dict, print out the key and the type of the value
 ```
 %% Cell type:code id: tags:
 ``` python
 # Warmup 4: Find the average age for our lecture
 sum_of_ages = 0
 lecture_name = "LEC003"
 num_people = 0
 for row in lecture_dict[lecture_name]:
    pass
 average = round(sum_of_ages/num_people, 3)
 print(lecture_name, average)
 ```
 %% Output
    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    <ipython-input-2-6a2163994cb9> in <module>
          4 lecture_name = "LEC003"
          5 num_people = 0
    ----> 6 for row in lecture_dict[lecture_name]:
          7     pass
          8
    NameError: name 'lecture_dict' is not defined
 %% Cell type:code id: tags:
 ``` python
 ```
 %% Cell type:code id: tags:
 ``` python
 # Warmup 5: Make a dictionary of each lecture's average age
 # the key is the lecture name
 # the value is the average age
 # tabbing the copied code
 # first just print out all the results,
 # then add to a dictionary
 lec_age_dict = {}
 for key in lecture_dict:
    print(key)
    # put code from above here
 lec_age_dict
 ```
 %% Output
    LEC001 19.932
    LEC002 19.867
    LEC003 19.356
    LEC004 19.407
    LEC005 19.958
    {'LEC001': 19.932,
     'LEC002': 19.867,
     'LEC003': 19.356,
     'LEC004': 19.407,
     'LEC005': 19.958}
 %% Cell type:code id: tags:
 ``` python
 ```
 %% Cell type:code id: tags:
 ``` python
 ```
 %% Cell type:code id: tags:
 ``` python
 ```
 %% Cell type:markdown id: tags:
-## March 11:  JSON Files
+## Lecture 19:  JSON Files
 Learning Objectives:
 - Interpret JSON formatted data and recognize differences between JSON and Python
 - Deserialize data from JSON for use in Python programs (read)
 - Serialize data into JSON for long term storage (write)
 %% Cell type:code id: tags:
 ``` python
 # We will be looking at lecture slides to understand JSON
 ```
 %% Cell type:code id: tags:
 ``` python
 # Deserialize
 def read_json(path):
    with open(path, encoding="utf-8") as f: # f is a varaible
        return json.load(f)                 # f represents a reference the JSON file
 # Serialize
 def write_json(path, data):
    with open(path, 'w', encoding="utf-8") as f:
        json.dump(data, f, indent=2)
 ```
 %% Cell type:code id: tags:
 ``` python
 # first, let's take a look at the file score_history.json
 ```
 %% Cell type:code id: tags:
 ``` python
 # now let's read it in and investigate the data
 scores_dict = read_json('score_history.json')
 #print(type(scores_dict))
 #print(scores_dict.keys())
 #print(scores_dict['bob'])
 #print(scores_dict)
 #scores_dict['andy'] = [17.0, 84.0]
 #print(scores_dict)
 ```
 %% Output
    <class 'dict'>
    dict_keys(['bob', 'alice', 'meena'])
    [20.0, 10.0]
    {'bob': [20.0, 10.0], 'alice': [30.0, 20.0], 'meena': [100.0, 10.0]}
    {'bob': [20.0, 10.0], 'alice': [30.0, 20.0], 'meena': [100.0, 10.0], 'andy': [17.0, 84.0]}
 %% Cell type:code id: tags:
 ``` python
 # Let's practice writing to a JSON file
 # when I'm testing code, I like to name my output file differently from my input file
 # so that I don't accidentally erase or overwrite my data
 write_json('score_history2.json', scores_dict)
 ```
 %% Cell type:markdown id: tags:
 ### We can make JSON files in many varied ways
 ### This makes a list of dictionaries
 %% Cell type:code id: tags:
 ``` python
 # Code from last lecture,
 # reads in the survey data into a list of dicts
 table_dict_list = []
 for i in range(len(rows)):
    row = rows[i]
    row_dict = {}
    for item in header: # iterate through each column name
        row_dict[item] = row[header.index(item)] # find the value in the row using .index
    print(row_dict)
    # add row_dict to table_dict_list
 table_dict_list # what is this? A ______ of _________
 ```
 %% Output
    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    <ipython-input-10-ebdc3b3869b4> in <module>
          2 # reads in the survey data into a list of dicts
          3 table_dict_list = []
    ----> 4 for i in range(len(rows)):
          5     row = rows[i]
          6     row_dict = {}
    NameError: name 'rows' is not defined
 %% Cell type:code id: tags:
 ``` python
 # Let's write this list of dictionaries into a JSON file
 write_json('cs220_as_json_list.json', table_dict_list)
 ```
 %% Cell type:code id: tags:
 ``` python
 # Verify:  can you find this file in your directory?
 ```
 %% Cell type:code id: tags:
 ``` python
 # let's write our original dictionary of lists - buckets into a JSON file
 write_json('cs220_as_json_dict.json', lecture_dict)
 ```
 %% Cell type:code id: tags:
 ``` python
 # Verify: can you find this file in your directory?
 ```
 %% Cell type:markdown id: tags:
 ### Many Web Sites have APIs that allow you to get their data
 ### Kiva.com Micro-lending site
 %% Cell type:code id: tags:
 ``` python
 # Take a look at kiva.json
 # read it into a dictionary
 kiva_dict = read_json('kiva.json')
 kiva_dict
 ```
 %% Output
    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    <ipython-input-12-2f403470e659> in <module>
          2
          3 # read it into a dictionary
    ----> 4 kiva_dict = read_json('kiva.json')
          5 kiva_dict
    NameError: name 'read_json' is not defined
 %% Cell type:code id: tags:
 ``` python
 # Plumbing the data
 kiva_dict['data'] # this gives us a list of dicts
 loan_list = None
 loan_list
 ```
 %% Output
    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    <ipython-input-11-07e7d0c7ba46> in <module>
          1 # Plumbing the data
    ----> 2 kiva_dict['data'] # this gives us a list of dicts
          3 loan_list = None
          4 loan_list
    NameError: name 'kiva_dict' is not defined
 %% Cell type:code id: tags:
 ``` python
 # what can we learn from this data?
 for loan_dict in loan_list:
    print(type(loan))
    for key in loan_dict:
        print(key)
 ```
 %% Output
    <class 'dict'>
    name
    description
    loanAmount
    geocode
    <class 'dict'>
    name
    description
    loanAmount
    geocode
    <class 'dict'>
    name
    description
    loanAmount
    geocode
    <class 'dict'>
    name
    description
    loanAmount
    geocode
    <class 'dict'>
    name
    description
    loanAmount
    geocode
 %% Cell type:code id: tags:
 ``` python
 # print out all the names
 for loan_dict in loan_list:
    print(loan_dict)
 ```
 %% Output
    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    <ipython-input-13-086b83d4d2f9> in <module>
          1 # print out all the names
    ----> 2 for loan_dict in loan_list:
          3     print(loan_dict)
    NameError: name 'loan_list' is not defined
 %% Cell type:code id: tags:
 ``` python
 # print out all the country names
 for loan_dict in loan_list:
    print(loan_dict)
 ```
 %% Output
    {'name': 'Albania', 'region': 'Eastern Europe', 'fundsLentInCountry': 9051250}
    {'name': 'Tajikistan', 'region': 'Asia', 'fundsLentInCountry': 64243075}
    {'name': 'Kenya', 'region': 'Africa', 'fundsLentInCountry': 120841775}
    {'name': 'Kenya', 'region': 'Africa', 'fundsLentInCountry': 120841775}
    {'name': 'Togo', 'region': 'Africa', 'fundsLentInCountry': 13719125}
 %% Cell type:code id: tags:
 ``` python
 # go to the kiva.com site and experiement with their API
 # https://www.kiva.org/build
 ```
 %% Cell type:markdown id: tags:
 ## After Lecture: Worksheet
 %% Cell type:code id: tags:
 ``` python
 ```

--- a/f22/andy_lec_notes/lec_19/lec19_worksheet_answers.ipynb
+++ b/f22/andy_lec_notes/lec_19/lec19_worksheet_answers.ipynb
--- a/f22/andy_lec_notes/lec_19/readme.md
+++ b/f22/andy_lec_notes/lec_19/readme.md
--- a/f22/andy_lec_notes/lec_19/score_history.json
+++ b/f22/andy_lec_notes/lec_19/score_history.json