Add files via upload

Author: daia-code

Week4/data.txt

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+course python1
+ course python2

Week4/data3.txt

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+hello

Week4/fisier.py

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+# file = open('data.txt', 'r+')
+# file.write("Hello")
+# file.close()
+
+# file=open('data3.txt','w')
+# try:
+#     file.write('hello')
+# finally:
+#     file.close()
+
+# with open('data.txt', 'w') as file:
+#     file.write('course python1\n course python2')
+
+# with open('data.txt', 'r') as file:
+#     for line in file.readlines():
+#         print(line, 'line')
+
+# with open('data.txt', 'r') as file:
+#     for line in list(file):
+#         print(line)
+
+with open('data.txt', 'r') as file:
+    while True:
+        line = file.readline()
+
+        if not line:
+            break
+        print(line)

Week4/pandas_exe.py

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+import pandas
+
+dataset = {
+    'masini': ["BMW", "DACIA", "FORD"],
+    "culoare": ["rosu", "negru", "gri"]
+}
+# variabila = pandas.DataFrame(dataset)
+# print(variabila)
+
+# culori = ["rosu", "negru", "gri"]
+# variabila = pandas.Series(culori, index=['x', 'y', 'z'])
+# print(variabila[0])
+# print(variabila)
+# print(variabila["z"], variabila[2])
+
+
+# dataset = {"BMW": "ROSU", "DACIA": "NEGRU", "FORD": "GRI"}
+# variabila = pandas.Series(dataset, index=["DACIA","FORD"])
+# print(variabila)
+variabila = pandas.DataFrame(dataset,index=["producator1","producator2","producator3"])
+# print(variabila.loc[0])
+# print(variabila.loc[[0,2]])
+# print(variabila.loc["producator1"])
+print(pandas.options.display.max_rows)
+

Week4/pandas_json.py

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+# import pandas as pd
+#
+# data = {
+#     "Duration": {
+#         "0": 60,
+#         "1": 60,
+#         "2": 60,
+#         "3": 45,
+#         "4": 45,
+#         "5": 60
+#     },
+#     "Pulse": {
+#         "0": 110,
+#         "1": 117,
+#         "2": 103,
+#         "3": 109,
+#         "4": 117,
+#         "5": 102
+#     },
+#     "Maxpulse": {
+#         "0": 130,
+#         "1": 145,
+#         "2": 135,
+#         "3": 175,
+#         "4": 148,
+#         "5": 127
+#     },
+#     "Calories": {
+#         "0": 409,
+#         "1": 479,
+#         "2": 340,
+#         "3": 282,
+#         "4": 406,
+#         "5": 300
+#     }
+# }
+#
+# df = pd.DataFrame(data)
+# # print(df.tail(2))
+# # print(df.head(2))
+# print(df.info())
+import pandas
+df = pandas.read_csv('test.csv')
+# print(df)
+# for x in df.index:
+  # print(df.loc[x, 'AL'])
+# print(df.corr())
+# print(df.describe())
+# print(df.mean())
+# import matplotlib.pyplot as mathplotvar
+# df.plot(kind="scatter", x='AT', y='BE')
+# df['AT'].plot(kind='hist')
+# mathplotvar.show()
+# print(df)
+df.fillna(0, inplace=True)
+# print(df)
+# print(df.fillna(0))
+# df['AL'].fillna(100, inplace=True)
+# print(df)
+# df.loc[7, 'AL'] = 45
+# print(df)
+df.replace(': ', 0, inplace=True)
+df.replace(':', 0, inplace=True)
+# print(df.transpose())
+print(df)
+df.to_csv('test1.csv')

Week4/test.csv

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+,AL,AT,BA,BE,BG,CH,CY
+0,: ,75 ,: ,77 ,45 ,:
+1,,79 ,: ,78 ,51 ,:
+2,: ,81 ,: ,80 ,54 ,:
+3,: ,81 ,: ,83 ,57 ,91 ,69
+4,: ,82 ,: ,82 ,59 ,: ,71
+5,: ,85 ,: ,85 ,64 ,: ,74
+6,: ,89 ,: ,86 ,67 ,93 b,79
+7,84 ,90 ,69 ,87 ,72 ,: ,86
+7,84 ,90 ,69 ,87 ,72 ,: ,86

Week4/test1.csv

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+,Unnamed: 0,AL,AT,BA,BE,BG,CH,CY
+0,0,0,75,0,77,45,0,0.0
+1,1,0,79,0,78,51,0,0.0
+2,2,0,81,0,80,54,0,0.0
+3,3,0,81,0,83,57,91 ,69.0
+4,4,0,82,0,82,59,0,71.0
+5,5,0,85,0,85,64,0,74.0
+6,6,0,89,0,86,67,93 b,79.0
+7,7,84 ,90,69 ,87,72,0,86.0
+8,7,84 ,90,69 ,87,72,0,86.0