day26

PureMachine · PureMachine · commit c49d5896b5ef · 2022-06-25T16:46:49.000-07:00
diff --git a/day26/main.py b/day26/main.py
@@ -0,0 +1,56 @@
+student_dict = {
+    "student": ["Angela", "James", "Lily"], 
+    "score": [56, 76, 98]
+}
+
+# Looping through dictionaries:
+# for (key, value) in student_dict.items():
+#     # Access key and value
+#     pass
+
+# student_data_frame = pandas.DataFrame(student_dict)
+
+# Loop through rows of a data frame
+# for (index, row) in student_data_frame.iterrows():
+#     # Access index and row
+#     # Access row.student or row.score
+#     pass
+
+# Keyword Method with iterrows()
+# {new_key:new_value for (index, row) in df.iterrows()}
+
+# TODO 1. Create a dictionary in this format:
+{"A": "Alfa", "B": "Bravo"}
+
+# TODO 2. Create a list of the phonetic code words from a word that the user inputs.
+
+import pandas
+
+nato_source = pandas.read_csv("nato_phonetic_alphabet.csv")
+
+def gen_nato():
+    nato = {row.letter: row.code for (index, row) in nato_source.iterrows()}
+    return nato
+
+
+def get_nato(nato_alpha, letter):
+    if letter != " ":
+        return nato_alpha[letter.upper()]
+    else:
+        return " "
+
+
+def take_input():
+    word = input("Enter a word to present as NATO alphabet: ")
+    return word
+
+
+def main():
+    nato = gen_nato()
+    word = take_input()
+    final = [get_nato(nato, letter) for letter in word]
+    print(final)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/day26/nato_phonetic_alphabet.csv b/day26/nato_phonetic_alphabet.csv
@@ -0,0 +1,27 @@
+letter,code
+A,Alfa
+B,Bravo
+C,Charlie
+D,Delta
+E,Echo
+F,Foxtrot
+G,Golf
+H,Hotel
+I,India
+J,Juliet
+K,Kilo
+L,Lima
+M,Mike
+N,November
+O,Oscar
+P,Papa
+Q,Quebec
+R,Romeo
+S,Sierra
+T,Tango
+U,Uniform
+V,Victor
+W,Whiskey
+X,X-ray
+Y,Yankee
+Z,Zulu
diff --git a/day26/scratch.py b/day26/scratch.py
diff --git a/states_game/learning.csv b/states_game/learning.csv
@@ -3,12 +3,12 @@
 1,Alaska
 2,Arizona
 3,Arkansas
-4,California
-5,Colorado
-6,Connecticut
-7,Delaware
-8,Florida
-9,Georgia
+4,Colorado
+5,Connecticut
+6,Delaware
+7,Florida
+8,Georgia
+9,Hawaii
 10,Idaho
 11,Illinois
 12,Indiana
@@ -25,25 +25,20 @@
 23,Missouri
 24,Montana
 25,Nebraska
-26,Nevada
-27,New Hampshire
-28,New Jersey
-29,New Mexico
-30,New York
-31,North Carolina
-32,North Dakota
-33,Oklahoma
-34,Oregon
-35,Pennsylvania
-36,Rhode Island
-37,South Carolina
-38,South Dakota
-39,Tennessee
-40,Texas
-41,Utah
-42,Vermont
-43,Virginia
-44,Washington
-45,West Virginia
-46,Wisconsin
-47,Wyoming
+26,New Hampshire
+27,New Jersey
+28,New York
+29,North Carolina
+30,North Dakota
+31,Oklahoma
+32,Pennsylvania
+33,Rhode Island
+34,South Carolina
+35,South Dakota
+36,Tennessee
+37,Utah
+38,Vermont
+39,Virginia
+40,West Virginia
+41,Wisconsin
+42,Wyoming
diff --git a/states_game/main.py b/states_game/main.py
@@ -18,10 +18,7 @@
 
 
 def cleanup():
-    all_states = state_data.state.to_list()
-    for state in all_states:
-        if state in guessed:
-            all_states.remove(state)
+    all_states = [state for state in state_data.state.to_list() if state not in guessed]
     data = {"state": all_states}
     pandas.DataFrame(data=data).to_csv("learning.csv")
 
