per category per year.txt

dff = pd.read_csv(r'C:\Users\NADA LABIB\Desktop\Analysis-of-Egyptian-Movies\data.csv', usecols=[' تاريخ العرض'])
#print(df)

prodYear = dff.values
date = []
for i in prodYear:
    date.append(i[0].split(' '))   
#print(date)    
    
    
def checkIfYear(y):
    if len(y)!= 4:
        return False
    for n in y :
        if not n.isdigit():
            return False
    return True

year = []
def takingYears(l):
    for i in range(len(l)):
        for j in range(len(l[i])):
            if checkIfYear(l[i][j]):
                year.append(l[i][j])
    return year

outputt = []            
outputt = takingYears(date)
outputtt = []
#outputtt = list( dict.fromkeys(outputt) )
#print(outputt)


appended = []
def append(o,m):
    for i in range(len(o)):
         appended.append(str(o[i])+":"+str(m[i]))
    return appended


nada = []
nada = append(outputt,filmTypes)
#print(nada)

final = []
def countingPerYear(m):
    for i in range(len(m)):
        counter = 0
        for j in range(len(m)):
            if m[i] == m[j]:
                counter += 1
        final.append(str(m[i])+":"+str(counter))
    return final
    
finall = []
finall = countingPerYear(nada)
finalll = list( dict.fromkeys(finall) )
#print(finalll)
\