Plot a distribution graph in Python

Question

I have written a function that does the job, however it looks particularly ugly. Would you give me some suggestion to make it more pythonic ? First of all I get some data from my database(via extractData). And then I have to do a check on every lenght after having calculating them.

Thus, I want to count every occurrences that last less than x days and plot it into matplotlib via bar.

Thanks for your help.

import numpy as np

listAct,less1,less2,less3,less4,less5,less6,less7,less8,less9=[],0,0,0,0,0,0,0,0,0
less10,less11,less12,less13,less14,sup14=0,0,0,0,0,0

for pos,rem in np.array(db.extractData(mess)):
    act = gen.unixTime_to_dateTime(rem)- gen.unixTime_to_dateTime(pos)
    lenAct = act.days  +act.seconds/float(86400)

    if lenAct < 1:
        less1+=1
    elif lenAct<2:
        less2+=1
    elif lenAct<3:
        less3+=1
    elif lenAct<4:
        less4+=1
    elif lenAct<5: 
        less5+=1
    elif lenAct<6:
        less6+=1
    elif lenAct<7:
        less7+=1
    elif lenAct<8:
        less8+=1
    elif lenAct<9:
        less9+=1 
    elif lenAct<10:
        less10+=1
    elif lenAct<11:
        less11+=1
    elif lenAct<12:
        less12+=1
    elif lenAct<13:
        less13+=1
    elif lenAct<14:
        less14+=1
    else:
        sup14+=1

    listAct.append(lenAct)    

study=[less1,less2,less3,less4,less5,less6,less7,less8,less9,less10,less11]
plt.bar(range(1,12),study)
plt.show()

Dirty_Fox · Accepted Answer · 2015-05-24 15:38:06Z

1

Matplotlib does pretty much everything :

import matplotlib.pyplot as plt
import numpy as np

listAct = []
for pos,rem in np.array(db.extractData(mess)):
    act = gen.unixTime_to_dateTime(rem)- gen.unixTime_to_dateTime(pos) ##act is a datetime object
    listAct.append(act.days + act.seconds/float(86400)) 

bins = range(1,15)
plt.hist(listAct,bins)
plt.show()

I hope this will help someone.

answered May 24, 2015 at 15:38

Dirty_Fox

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