In this problem, you are asked to implement a function to get the player's shots data. In particular, your function should read in "data/shot_logs.csv" and filter the dataset to return the player's data.

In [1]:

import pandas as pd

def GetPlayerData(player):

 df_shots_player = None

 # YOUR CODE HERE

 raise NotImplementedError()

 return df_shots_player

In [2]:

df_shots_player = GetPlayerData("stephen curry")

assert df_shots_player.shape == (968, 21)

df_shots_player = GetPlayerData("brian roberts")

assert df_shots_player.shape == (372, 21)

Problem 2

You need to implement a function to add a Month column to the existing data, which contains the month from the MATCHUP column.

In [ ]:

def AddMonth(df_shots_player):

 d = {'JAN':1, 'FEB':2, 'MAR':3, 'APR':4, 'MAY':5, 'JUN': 6, 'JUL':7,'AUG':8,'SEP':9,'OCT':10,'NOV':11,'DEC':12 }

 # YOUR CODE HERE

 return df_shots_player

In [ ]:

df_shots_player = GetPlayerData("stephen curry")

df_shots_player = AddMonth(df_shots_player)

assert round(df_shots_player["Month"].describe()["mean"], 2) == 6.65

df_shots_player = AddMonth(GetPlayerData("brian roberts"))

assert round(df_shots_player["Month"].describe()["mean"], 2) == 6.69

Problem 3

You need to implement a function to add a column called "Short_Type" to df_shots_player that identifies the shot type as one of the three that we are interested in: "short" (

In [ ]:

def GetShotType(row):

 """

 This function takes a row of the dataset and returns

 "3-pointer", "short" or "mid-range" depending on the shot

 type.

 """

 return_type = "3-pointer"

 # YOUR CODE HERE

 raise NotImplementedError()

 return return_type

def AddShotType(df_shots_player):

 # YOUR CODE HERE

 raise NotImplementedError()

 return df_shots_player

In [ ]:

import pandas as pd

df_shots_player = GetPlayerData("stephen curry")

df_shots_player = AddMonth(df_shots_player)

df_shots_player = AddShotType(df_shots_player)

assert df_shots_player[df_shots_player["Shot_Type"] == "3-pointer"].shape[0] == 456

assert df_shots_player[df_shots_player["Shot_Type"] == "short"].shape[0] == 224

assert df_shots_player[df_shots_player["Shot_Type"] == "mid-range"].shape[0] == 288

Problem 4

You need to implement a function to compute the player's field goal percentage for each month and for each type of shot. Only look at months where he took at least 30 shots in each category. The function should return a dataframe for "stephen curry" as the follows:

In [ ]:

def ComputeGoalType(df_shots_player):

 FG_perc_by_month = None

 # YOUR CODE HERE

 return FG_perc_by_month

In [ ]:

df_shots_player = GetPlayerData("stephen curry")

df_shots_player = AddMonth(df_shots_player)

df_shots_player = AddShotType(df_shots_player)

FG_perc_by_month = ComputeGoalType(df_shots_player)

assert [round(x, 2) for x in FG_perc_by_month["3-pointer"].tolist()] == [0.41, 0.47, 0.43, 0.35]

assert [round(x, 2) for x in FG_perc_by_month["short"].tolist()] == [0.65, 0.65, 0.65, 0.70]

The CSV File is in the shared link

https://drive.google.com/file/d/1scO0JF15YX0K3r17T6oNRBd1VV7wLojz/view?usp=sharing

Problem 1 In this problem, you are asked to implement a function to get the player's shots data. In particular, your function should read in "data/shot_logs.csv" and filter the dataset to return the player's data. In [1]: import pandas as pd def GetPlayerData(player): df_shots_player = None \# YOUR CODE HERE raise NotImplementedError() return df_shots_player In [2]: df_shots_player = GetPlayerData("stephen curry") assert df_shots_player.shape ==(968,21) df_shots_player = GetPlayerData("brian roberts") assert df _shots_player.shape ==(372,21) Problem 2 You need to implement a function to add a Month column to the existing data, which contains the month from the MATCHUP column. You need to implement a function to add a column called "Short_Type" to df_shots_player that identifies the shot type as one of the three that we are interested in: "short" (