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This repository was archived by the owner on Apr 17, 2023. It is now read-only.

Commit 063b468

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7 files changed

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‎Week4/data.txt‎

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course python1
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course python2

‎Week4/data3.txt‎

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hello

‎Week4/fisier.py‎

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

‎Week4/pandas_exe.py‎

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import pandas
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dataset = {
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'masini': ["BMW", "DACIA", "FORD"],
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"culoare": ["rosu", "negru", "gri"]
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}
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# variabila = pandas.DataFrame(dataset)
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# print(variabila)
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# culori = ["rosu", "negru", "gri"]
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# variabila = pandas.Series(culori, index=['x', 'y', 'z'])
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# print(variabila[0])
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# print(variabila)
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# print(variabila["z"], variabila[2])
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# dataset = {"BMW": "ROSU", "DACIA": "NEGRU", "FORD": "GRI"}
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# variabila = pandas.Series(dataset, index=["DACIA","FORD"])
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# print(variabila)
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variabila = pandas.DataFrame(dataset,index=["producator1","producator2","producator3"])
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# print(variabila.loc[0])
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# print(variabila.loc[[0,2]])
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# print(variabila.loc["producator1"])
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print(pandas.options.display.max_rows)
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‎Week4/pandas_json.py‎

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

‎Week4/test.csv‎

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

‎Week4/test1.csv‎

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

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