def getPitStops(filepath):
"""
Parameters
----------
filepath: string
The directory to the file relative to the parentPath
# [raceId, driverId, stop, lap, time, duration, milliseconds]
Returns
-------
tuple
(headings, data, dictionary)
"""
RecentDriversList = getRecentDrivers(2000)
circuitRaceList = getCircuitRaceList("races.csv")
circuitRaceKeys = circuitRaceList.keys()
PitStopsData = getDataset(filepath)
dataObtained = PitStopsData.next()
Data = []
for data in PitStopsData:
if (ifExist(data[1], RecentDriversList)):
for key in circuitRaceKeys:
if (data[0] in circuitRaceList[key]):
Data.append(data)
# Data = list(PitStopsData)
print "Data from file: " + str(dataObtained)
# print "Data Extracted: " + 'Year ' + " raceID"
_ret_dict = defaultdict(lambda: defaultdict(lambda: 0.0))
for d in Data:
# {raceId, driverId :{ stop: pit time }}
_ret_dict[str(d[0]) + "," + str(d[1])][d[2]] = d[6]
return (dataObtained, Data, _ret_dict)
def getPreprocessedData(filepath):
"""
Parameters
----------
filepath: string
The directory to the file relative to the parentPath
# [raceId, driverId, constructorId, rank, points, grid, position, positionOrder, positionText , firstLapChange, pitStops]
Returns
-------
tuple
(headings, data, dictionary)
"""
RecentDriversList = getRecentDrivers(2000)
circuitRaceList = getCircuitRaceList("races.csv")
circuitRaceKeys = circuitRaceList.keys()
PreprocessedData = getDataset(filepath)
dataObtained = PreprocessedData.next()
# Data = list(PreprocessedData)
Data = []
for data in PreprocessedData:
if (ifExist(data[1], RecentDriversList)):
for key in circuitRaceKeys:
if (data[0] in circuitRaceList[key]):
Data.append(data)
print "Data from file: " + str(dataObtained)
return (dataObtained, Data)
def getDataFromResults(filepath):
"""
Parameters
----------
filepath: string
The directory to the file relative to the parentPath
# [raceID, driverID, constructorID, rank, points, grid, postion, positionOrder]
Returns
-------
tuple
(headings, data)
"""
RecentDriversList = getRecentDrivers(2000)
circuitRaceList = getCircuitRaceList("races.csv")
circuitRaceKeys = circuitRaceList.keys()
ResultData = getDataset(filepath)
dataObtained = ResultData.next()
Data = []
# Data = list(ResultData)
for data in ResultData:
if (ifExist(data[1], RecentDriversList)):
for key in circuitRaceKeys:
if (data[0] in circuitRaceList[key]):
Data.append(data)
print "Data from file: " + str(dataObtained)
# print "Data Extracted: " + 'Year ' + " raceID"
# yearDict_raceList = defaultdict(lambda:[]) # initialise the dictionary value to an empty list
# dataObtained.append("firstLapChange")
# for d in Data:
# d.append(int(d[5]) - int(d[7]))
return (dataObtained, Data)
def getLapTimes(filepath):
"""
Parameters
----------
filepath: string
The directory to the file relative to the parentPath
# [raceId, driverId, lap, position, time, milliseconds]
Returns
-------
tuple
(headings, data, dictionary, dictionary of dictionary)
"""
RecentDriversList = getRecentDrivers(2000)
circuitRaceList = getCircuitRaceList("races.csv")
circuitRaceKeys = circuitRaceList.keys()
LapTimesData = getDataset(filepath)
dataObtained = LapTimesData.next()
# Data = list(LapTimesData)
Data = []
for data in LapTimesData:
if (ifExist(data[1], RecentDriversList)):
for key in circuitRaceKeys:
if (data[0] in circuitRaceList[key]):
Data.append(data)
print "Data from file: " + str(dataObtained)
# {raceID: [[driverID, lap#, laptime]]}
_ret_dict = defaultdict(lambda: [])
# {raceID: {lap#: [driverID, laptime]}}
_ret_dict_dict = defaultdict(lambda: defaultdict(lambda: []))
for d in Data:
# {raceId, driverId :{ lap: laptime]]
# _ret_dict[str(d[0]) +"," + str(d[1])][d[2]] = d[5]
_ret_dict[int(d[0])].append(np.array([int(d[1]),
int(d[2]),
int(d[5])]))
# {raceID: {lap#: [driverID, laptime]}}
_ret_dict_dict[int(d[0])][int(d[2])].append([int(d[1]), int(d[5])])
# keys = sorted(_ret_dict_dict.keys(), lambda _key: int(_key))
keys = _ret_dict_dict.keys()
for key in keys:
_keys = _ret_dict_dict[key].keys()
for _key in _keys:
_ret_dict_dict[key][_key].sort(key=itemgetter(1))
# print _ret_dict_dict[key][_key]
return (dataObtained, Data, _ret_dict, _ret_dict_dict)
def getCircuitSpecificStatisticsOfFirstLapChange(headings):
"""
for circuit specific statistics
"""
headings.append("DriverId")
headings.append("DriverName")
headings.append("CircuitId")
headings.append("CircuitName")
headings.append("FirstLapChangeList")
headings.append("FirstLapChangeMin")
headings.append("FirstLapChangeMax")
headings.append("FirstLapChangeFirstQuartile")
headings.append("FirstLapChangeMedian")
headings.append("FirstLapChangeThirdQuartile")
headings.append("FirstLapChangeMean")
headings.append("FirstLapChangeSd")
_ret_list = []
circuitRaceList = getCircuitRaceList("races.csv")
PreprocessedDataHeadings, PreprocessedDataset = getPreprocessedData(
"PreprocessedDataset1.csv")
circuitNameDict = getRecentTracksName()
driverIDNameDict = getDriverIDName("drivers.csv")
# temperary data structure
# {driverId: {circuitId: [first lap change]}}
_dict_dict_list = defaultdict(lambda: defaultdict(lambda: []))
for data in PreprocessedDataset:
circuitKeys = circuitRaceList.keys()
for circuitKey in circuitKeys:
if (data[0] in circuitRaceList[circuitKey]):
_dict_dict_list[data[1]][circuitKey].append(data[9])
# print _dict_dict_list["4"]["32"]
driversKeys = sorted(_dict_dict_list.keys(), key=lambda _key: int(_key))
for driversKey in driversKeys:
_driverID = driversKey
_driverName = driverIDNameDict[_driverID]
_circuitID = ""
_circuitName = ""
_FirstLapChangeList = ""
_FirstLapChangeMin = 0.0
_FirstLapChangeMax = 0.0
_FirstLapChangeFirstQuartile = 0.0
_FirstLapChangeMedian = 0.0
_FirstLapChangeThirdQuartile = 0.0
_FirstLapChangeMean = 0.0
_FirstLapChangeSd = 0.0
driverCircuitsKeys = sorted(_dict_dict_list[driversKey].keys(),
key=lambda _key: int(_key))
for driverCircuitsKey in driverCircuitsKeys:
# _tempSumOfFirstLapChange = 0.0;
_tempContainer = []
_circuitID = driverCircuitsKey
_circuitName = circuitNameDict[_circuitID]
for firstLapChangeVal in _dict_dict_list[driversKey][
driverCircuitsKey]:
if (firstLapChangeVal != "-999"):
_FirstLapChangeList += (firstLapChangeVal + ",")
_change = int(firstLapChangeVal)
_tempContainer.append(_change)
_tempContainer.sort(key=lambda _key: int(_key))
if (len(_tempContainer) != 0):
_FirstLapChangeMin = _tempContainer[0]
_FirstLapChangeMax = _tempContainer[-1]
_FirstLapChangeFirstQuartile = _tempContainer[
len(_tempContainer) / 4]
_FirstLapChangeMedian = _tempContainer[len(_tempContainer) / 2]
_FirstLapChangeThirdQuartile = _tempContainer[
len(_tempContainer) / 4 * 3]
_FirstLapChangeMean = np.sum(
np.array(_tempContainer)) / len(_tempContainer)
_FirstLapChangeSd = np.sqrt(
np.sum((
(np.array(_tempContainer) - _FirstLapChangeMean)**2)) /
len(_tempContainer))
_ret_list.append([
_driverID, _driverName, _circuitID, _circuitName,
_FirstLapChangeList, _FirstLapChangeMin, _FirstLapChangeMax,
_FirstLapChangeFirstQuartile, _FirstLapChangeMedian,
_FirstLapChangeThirdQuartile, _FirstLapChangeMean,
_FirstLapChangeSd
])
# print _FirstLapChangeList
# if(len(_tempContainer) != 0):
# _FirstLapChangeMin=_tempContainer[0]
# _FirstLapChangeMax=_tempContainer[-1]
# _FirstLapChangeFirstQuartile = _tempContainer[len(_tempContainer)/4]
# _FirstLapChangeMedian=_tempContainer[len(_tempContainer)/2]
# _FirstLapChangeThirdQuartile = _tempContainer[len(_tempContainer)/4 *3]
# _FirstLapChangeMean=np.sum(np.array(_tempContainer))/len(_tempContainer)
# _FirstLapChangeSd=np.sqrt(np.sum(((np.array(_tempContainer)-_FirstLapChangeMean)**2))/len(_tempContainer))
# _ret_list.append([_driverID, _FirstLapChangeList, _FirstLapChangeMin, _FirstLapChangeMax, _FirstLapChangeFirstQuartile,
# _FirstLapChangeMedian, _FirstLapChangeThirdQuartile, _FirstLapChangeMean, _FirstLapChangeSd])
_ret_list.insert(0, headings)
saveLListAsCSV("PreprocessedDataset3", _ret_list)
def getDriverIDConstructorAveragePointsRanking(dataset):
"""
Parameters:
-----------
dataset:
#[raceID, driverID, constructorID, rank, points]
"""
# print "dataset"
# print dataset
def returnCategoryNumber(rank):
if(int(rank) == 1):
# print "1"
return 4
if((int(rank) > 1) & (int(rank) < 4)):
# print "2-3"
return 3
if((int(rank) > 3) & (int(rank) < 11)):
# print "4-10"
return 2
return 1
_listOfList = [["ConstructorName", "DriverID", "DriverName","CircuitName", "AveragePoints", "Ranking Groups"]]
# {driverID: {constructorID: points}}
# _temp = defaultdict(lambda:defaultdict(lambda:float(0)))
# {driverID: totalpoints}
_totalpoints = defaultdict(lambda:float(0))
circuitRaceList = getCircuitRaceList("races.csv")
_circuitRaceList_keys = sorted(circuitRaceList.keys(), key = lambda _key: int(_key))
circuitIDNameDict = getRecentTracksName()
# {constructorID: [driverID]}
# _consDriver = defaultdict(lambda:[])
# get number of collaborations in terms of years
# {constructor: {driverID: [raceID]}}
# Step 1: get {constructor: {driverID: [year]}}
# _consDriverYear = defaultdict(lambda:defaultdict())
# _consDriverRaceID = defaultdict(lambda:defaultdict(lambda:[]))
# Step 1: get {driverID: [raceID]}
# Step 2: convert to {driverID:[year]}
# Step 1 #
_driverRace = defaultdict(lambda:[])
for data in dataset:
# _temp[data[1]][data[2]] += float(data[4])
_totalpoints[data[1]] += float(data[4])
# _consDriver[data[2]].append(data[1])
# _consDriverRaceID[data[2]][data[1]].append(data[0])
_driverRace[data[1]].append(data[0])
yearDict_raceList = getYearRaceID("races.csv")
ConstructorIDName = getConstructorIDName("constructors.csv")
DriverName = getDriverIDName("drivers.csv")
# Step 2 #
_driverYear = convertRaceToYear(_driverRace, yearDict_raceList)
# keys_CDR = sorted(_consDriverRaceID.keys(), key = lambda _key: int(_key))
# # Step 2 #
# for key_CDR in keys_CDR:
# _temp_DriverYear = convertRaceToYear(_consDriverRaceID[key_CDR], yearDict_raceList)
# keys_temp_DY = sorted(_temp_DriverYear.keys(), key= lambda _key: int(_key))
# for key_temp_DY in keys_temp_DY:
# _consDriverYear[key_CDR][key_temp_DY] = _temp_DriverYear[key_temp_DY]
# dict_of_list {driverID: [raceID, starting position, position after first lap, ending position]}
_dict_grid_firstLapPosition_finalPosition = getRaceID_Grid_FirstLapPosition_FinalPosition()
for data in dataset:
rank = 0
_circuitID = "";
for raceIDStats in _dict_grid_firstLapPosition_finalPosition[data[1]]:
if(raceIDStats[0] == data[0]):
rank = int(raceIDStats[3]) - int(raceIDStats[1])
break
for _circuitRaceList_key in _circuitRaceList_keys:
if(data[0] in circuitRaceList[_circuitRaceList_key]):
_circuitID = _circuitRaceList_key
break
_listOfList.append([ConstructorIDName[data[2]],\
data[1], \
DriverName[data[1]],\
circuitIDNameDict[_circuitID],\
_totalpoints[data[1]]/len(_driverYear[data[1]]),\
returnCategoryNumber(rank)
])
return {"listofList": _listOfList}
def getDriverTopPerformingCircuits():
def returnCategory(rank):
if(int(rank) == 1):
# print "1"
return "1"
if((int(rank) > 1) & (int(rank) < 4)):
# print "2-3"
return "2_3"
if((int(rank) > 3) & (int(rank) < 11)):
# print "4-10"
return "4_10"
return "others"
# step one temp data structure {driverID: {rank: {circuitId: count}}}
_tempCountDict = defaultdict(lambda:defaultdict(lambda:defaultdict(lambda:0)))
# step two temp data structure {driverID: {rank: [circuitId, count]}}
_tempCountList = defaultdict(lambda:defaultdict(lambda:[]))
# return list [driverID, _ranking, circuit_id]
_ret_list = []
# return list [driverID, _ranking, circuit_id, count]
_ret_list_count = []
circuitRaceList = getCircuitRaceList("races.csv") # {circuitID: raceList}
RGFF_dict = getRaceID_Grid_FirstLapPosition_FinalPosition() # {driverID: [ raceID, starting position, position after first lap, final position]}
# print circuitRaceList
# print RGFF_dict
_RGFF_dict_keys = sorted(RGFF_dict.keys(), key = lambda _key: int(_key))
_circuitRace_keys = sorted(circuitRaceList.keys(), key = lambda _key: int(_key))
# print _RGFF_dict_keys
# print _circuitRace_keys
for _rkey in _RGFF_dict_keys:
for _ckey in _circuitRace_keys:
# print (RGFF_dict[_rkey])
# print circuitRaceList[_ckey]
for _driverInfo in RGFF_dict[_rkey]:
if(_driverInfo[0] in circuitRaceList[_ckey]):
# print RGFF_dict[_rkey][3]
_tempCountDict[_rkey][returnCategory(_driverInfo[3])][_ckey] += 1
# print _tempCountDict
driverIDKeys = sorted(_tempCountDict.keys(), key = lambda _key: int(_key))
for _dikey in driverIDKeys:
rankingKeys = _tempCountDict[_dikey].keys()
for _rkey in rankingKeys:
circuitKeys = _tempCountDict[_dikey][_rkey].keys()
for _ckey in circuitKeys:
_temp_2Dlist = [_ckey,_tempCountDict[_dikey][_rkey][_ckey]]
# _tempCountList[_dikey][_rkey][0] = _ckey
# _tempCountList[_dikey][_rkey][1] = _tempCountDict[_dikey][_rkey][_ckey]
_tempCountList[_dikey][_rkey].append(_temp_2Dlist)
_tempCountList[_dikey][_rkey].sort(key=itemgetter(1), reverse = True)
driverIDKeys = sorted(_tempCountList.keys(), key = lambda _key: int(_key))
for _dikey in driverIDKeys:
rankingKeys = _tempCountList[_dikey].keys()
for _rkey in rankingKeys:
breakCount = 0
# print _tempCountList[_dikey][_rkey]
_temp_top3Circuits = ""
for listData in (_tempCountList[_dikey][_rkey]):
_temp_top3Circuits += ( "_" + str(listData[0]))
breakCount += 1
if(breakCount > 2):
break
_ret_list.append([_dikey, _rkey, _temp_top3Circuits])
return _ret_list
