列に基づいたプロット

Question

私はこのデータセット（panda df）をよく捉えていますが、これは構造体です。

Replication     State Machine Average Time Std. Percent 
      1     IDLE bend  1.0863   68.42 
      1 State Bend real failur bend  19.7653   8.24 
      1     BUSY bend  0.3144   19.88 
      1 State Bend Die change bend  25.0000   3.47 
      2 State Bend Die change bend  25.0000   3.47 
      2 State Bend real failur bend  20.4153   6.88 
      2     BUSY bend  0.3058   19.93 
      2     IDLE bend  1.0742   69.73 
      3     IDLE bend  1.0803   69.25 
      3 State Bend Die change bend  25.0000   3.47 
      3 State Bend real failur bend  19.4699   7.23 
      3     BUSY bend  0.3117   20.04 

私がしたいことは、4つのヒストグラム（状態毎に1つ）を作ることです。私は、x軸上の複製と、 "Std。 「パーセント」または「平均時間」がy軸の上に表示されます。誰がどのようにプロットすることができるかについていくつかの洞察力を与えることができますか？

これは私がこれまでに作られたコードは、私はそれが1で動作するようにしたいので、私は、任意のループを行っていないですし、私ことができるように私は、コードを持って

import pandas as pd 
import matplotlib.pyplot as plt 

data = pd.read_csv('frequencies50cleaned.csv', sep=',') 
data.columns= ['Replication', 'State', 'Machine', 'Average Time','Std. Percent'] 


bend = data[data['Machine'] == 'bend'] 
punch = data[data['Machine'] == 'punch'] 
form = data[data['Machine'] == 'form'] 
shear = data[data['Machine'] == 'shear'] 

bend = bend.sort(columns='Replication') 
x = bend[bend['State'] == 'IDLE']['Replication'] 
y = bend[bend['State'] == 'IDLE']['Std. Percent'] 

punch = punch.sort(columns='Replication') 
z = punch[punch['State'] == 'IDLE']['Replication'] 
p = punch[punch['State'] == 'IDLE']['Std. Percent'] 

bend.hist(column=['Replication']) 
#plt.clf() 
#plt.plot(x,y) 
#plt.plot(z,p) 
#plt.show() 

Answer 1

すべてのあとがきをループ作業。私はそれをここに掲載します、そして、できれば他のNP

# Prefix for the scenario 
scen_name = "scenario1" 

# Importing the Data 
data = pd.read_csv(scen_name+'_frequencies50limcleaned.csv', sep=',') 
data.columns= ['Replication', 'State', 'Machine', 'Average Time','Std. Percent'] 

# Conforming the data 
data.State = data.State.replace('State Bend Blocked', 'Blocked') 
data.State = data.State.replace('State Punch Blocked', 'Blocked') 
data.State = data.State.replace('State Shear Blocked', 'Blocked') 
data.State = data.State.replace('State Form Blocked', 'Blocked') 

data.State = data.State.replace('State Bend real failur', 'Real Failure') 
data.State = data.State.replace('State Punch real failur', 'Real Failure') 
data.State = data.State.replace('State Shear real failur', 'Real Failure') 
data.State = data.State.replace('State Form real failur', 'Real Failure') 

data.State = data.State.replace('State Bend Die change', 'Die Change') 
data.State = data.State.replace('State Punch Die change', 'Die Change') 
data.State = data.State.replace('State Shear Die change', 'Die Change') 
data.State = data.State.replace('State Form Die change', 'Die Change') 

# Splitting data on machine 
bend = data[data['Machine'] == 'bend'] 
punch = data[data['Machine'] == 'punch'] 
form = data[data['Machine'] == 'form'] 
shear = data[data['Machine'] == 'shear'] 

report_vals = ['Average Time', 'Std. Percent'] 
states = ['IDLE', 'BUSY', 'Blocked'] 
post_fixes = ['avg_time', 'percent'] 
titles = ['Average time in state: ','Frequencies of in percent: '] 

i = 0 
for rep in report_vals: 
    for state in states: 
     bend = bend.sort_values('Replication') 
     x = bend[bend['State'] == state]['Replication'] 
     punch = punch.sort_values('Replication') 
     y = punch[punch['State'] == state]['Replication'] 
     form = form.sort_values('Replication') 
     z = form[form['State'] == state]['Replication'] 
     shear = shear.sort_values('Replication') 
     w = shear[shear['State'] == state]['Replication'] 

     b = bend[bend['State'] == state][rep] 
     p = punch[punch['State'] == state][rep] 
     f = form[form['State'] == state][rep] 
     s = shear[shear['State'] == state][rep] 

     fig, ax = plt.subplots() 

     rects1 = plt.plot(x,b,'b', 
         label='Bend') 

     rects2 = plt.plot(y,p,'g', 
         label='Punch') 

     rects3 = plt.plot(z,f,'r', 
         label='Form') 

     rects4 = plt.plot(w,s,'y', 
         label='Shear') 

     plt.xlabel('Replication') 
     plt.ylabel(rep) 
     plt.title(titles[i]+state) 
     plt.legend() 

     plt.tight_layout() 
     plt.savefig('/home/misterwhite/Dropbox/Aarhus Universitet/8. Semester/Modellering, simulation og analyse/Arena Project/Report/images/'+scen_name+'_'+state+'_'+post_fixes[i]+'.png') 
    i +=1