python_class/New_Pandas.py at Matrix · harinivbaskar/python_class · GitHub

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# import pandas

# mydataset = {
#     "cars" : ["BMW", "Volvos", "Ford"],
#     "passings" : [3, 7, 2]
# }

# myvar = pandas.DataFrame(mydataset)

# print(myvar)

"---------------------------------------------"

# import pandas as pd

# mydataset = {
#     "cars" : ["BMW", "Volvos", "Ford"],
#     "passings" : [3, 7, 2]
# }

# myvar = pd.DataFrame(mydataset)

# print(myvar)

"---------------------------------------------"

# import pandas as pd

# print(pd.__version__)

"---------------------------------------------"

# import pandas as pd

# a = [1, 7, 2]

# myvar = pd.Series(a)

# print(myvar)

# print(myvar[1])

"---------------------------------------------"

# import pandas as pd

# a = [1, 7, 2]

# myvar = pd.Series(a, index = ["x", "y", "z"])

# print(myvar)

# print(myvar["y"])

"---------------------------------------------"

# import pandas as pd

# calories = {"day1": 420, "day2": 380, "day3": 390}

# myvar = pd.Series(calories)

# print(myvar)

"---------------------------------------------"

# import pandas as pd

# calories = {"day1": 420, "day2": 380, "day3": 390}

# myvar = pd.Series(calories, index = ["day1", "day2"])

# print(myvar)

"---------------------------------------------"

# import pandas as pd

# data = {
#     "calories" : [420, 380, 390],
#     "duration" : [50, 40, 45]
# }

# df = pd.DataFrame(data)

# print(df)

# print(df.loc[0])

# print(df.loc[[0, 1]])

"---------------------------------------------"

# import pandas as pd

# data = {
#     "calories" : [420, 380, 390],
#     "duration" : [50, 40, 45]
# }

# df = pd.DataFrame(data, index = ["day", "day2", "day3"])

# print(df)

# print(df.loc["day2"])

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv("C:\\Users\\harin\\python_class\\Automobile_data.csv")

# print(df)

# print(df.to_string())

"---------------------------------------------"

# import pandas as pd

# print(pd.options.display.max_rows)

"---------------------------------------------"

# import pandas as pd

# pd.options.display.max_rows = 9999

# df = pd.read_csv("C:\\Users\\harin\\python_class\\Automobile_data.csv")

# print(df)

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv("C:\\Users\\harin\\python_class\\data.csv")

# print(df)

# print(df.to_string())

"---------------------------------------------"

# import pandas as pd

# print(pd.options.display.max_rows)

"---------------------------------------------"


# import pandas as pd

# pd.options.display.max_rows = 9999

# df = pd.read_csv("C:\\Users\\harin\\python_class\\data.csv")

# print(df)

"---------------------------------------------"

# import pandas as pd

# df = pd.read_json('C:\\Users\\harin\\python_class\\data.json')

# print(df.to_string())

"---------------------------------------------"

# 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)

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv('data.csv')

# new_df = df.dropna()

# print(new_df.to_string())

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv('data.csv')

# df.dropna(inplace = True)

# print(df.to_string())

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv('data.csv')

# df.fillna(130, inplace = True)

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv('data.csv')

# df["Calories"].fillna(130, inplace = True)

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv('data4.csv')

# df.dropna(subset=['Date  Pulse'], inplace = True)

# print(df.to_string())

"---------------------------------------------"

# import pandas as pd

# df = pd.read_csv('data5.csv')

# print(df.corr())

"---------------------------------------------"

# import pandas as pd
# import matplotlib.pyplot as plt

# df = pd.read_csv("data5.csv")

# df.plot()

# plt.show()

"---------------------------------------------"

# import pandas as pd
# import matplotlib.pyplot as plt

# df = pd.read_csv("data5.csv")

# df.plot(kind = "scatter", x = "Duration", y = "Calories")

# plt.show()

"---------------------------------------------"

# import pandas as pd
# import matplotlib.pyplot as plt

# df = pd.read_csv("data5.csv")

# df.plot(kind = "scatter", x = "Duration", y = "Maxpulse")

# plt.show()

"---------------------------------------------"

# import sys
# import matplotlib
# matplotlib.use('Agg')

# import pandas as pd
# import matplotlib.pyplot as plt

# df = pd.read_csv('data5.csv')

# df["Duration"].plot(kind = 'hist')

# plt.show()

# # plt.savefig(sys.stdout.buffer)
# # sys.stdout.flush()

# # install seaborn

"---------------------------------------------"

# import pandas as pd
# import matplotlib.pyplot as plt

# df = pd.read_csv('data5.csv')

# df["Duration"].plot(kind = 'hist')

# plt.show()

"---------------------------------------------"