-
Notifications
You must be signed in to change notification settings - Fork 0
/
Plot_AQI.py
160 lines (138 loc) · 4.45 KB
/
Plot_AQI.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
import pandas as pd
import matplotlib.pyplot as plt
def avg_data_2013():
temp_i=0
average=[]
for rows in pd.read_csv('Data/AQI/aqi2013.csv',chunksize=24):
add_var=0
avg=0.0
data=[]
df=pd.DataFrame(data=rows)
for index,row in df.iterrows():
data.append(row['PM2.5'])
for i in data:
if type(i) is float or type(i) is int:
add_var=add_var+i
elif type(i) is str:
if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
temp=float(i)
add_var=add_var+temp
avg=add_var/24
temp_i=temp_i+1
average.append(avg)
return average
def avg_data_2014():
temp_i=0
average=[]
for rows in pd.read_csv('Data/AQI/aqi2014.csv',chunksize=24):
add_var=0
avg=0.0
data=[]
df=pd.DataFrame(data=rows)
for index,row in df.iterrows():
data.append(row['PM2.5'])
for i in data:
if type(i) is float or type(i) is int:
add_var=add_var+i
elif type(i) is str:
if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
temp=float(i)
add_var=add_var+temp
avg=add_var/24
temp_i=temp_i+1
average.append(avg)
return average
def avg_data_2015():
temp_i=0
average=[]
for rows in pd.read_csv('Data/AQI/aqi2015.csv',chunksize=24):
add_var=0
avg=0.0
data=[]
df=pd.DataFrame(data=rows)
for index,row in df.iterrows():
data.append(row['PM2.5'])
for i in data:
if type(i) is float or type(i) is int:
add_var=add_var+i
elif type(i) is str:
if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
temp=float(i)
add_var=add_var+temp
avg=add_var/24
temp_i=temp_i+1
average.append(avg)
return average
def avg_data_2016():
temp_i=0
average=[]
for rows in pd.read_csv('Data/AQI/aqi2016.csv',chunksize=24):
add_var=0
avg=0.0
data=[]
df=pd.DataFrame(data=rows)
for index,row in df.iterrows():
data.append(row['PM2.5'])
for i in data:
if type(i) is float or type(i) is int:
add_var=add_var+i
elif type(i) is str:
if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
temp=float(i)
add_var=add_var+temp
avg=add_var/24
temp_i=temp_i+1
average.append(avg)
return average
def avg_data_2017():
temp_i=0
average=[]
for rows in pd.read_csv('Data/AQI/aqi2017.csv',chunksize=24):
add_var=0
avg=0.0
data=[]
df=pd.DataFrame(data=rows)
for index,row in df.iterrows():
data.append(row['PM2.5'])
for i in data:
if type(i) is float or type(i) is int:
add_var=add_var+i
elif type(i) is str:
if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
temp=float(i)
add_var=add_var+temp
avg=add_var/24
temp_i=temp_i+1
average.append(avg)
return average
def avg_data_2018():
temp_i=0
average=[]
for rows in pd.read_csv('Data/AQI/aqi2018.csv',chunksize=24):
add_var=0
avg=0.0
data=[]
df=pd.DataFrame(data=rows)
for index,row in df.iterrows():
data.append(row['PM2.5'])
for i in data:
if type(i) is float or type(i) is int:
add_var=add_var+i
elif type(i) is str:
if i!='NoData' and i!='PwrFail' and i!='---' and i!='InVld':
temp=float(i)
add_var=add_var+temp
avg=add_var/24
temp_i=temp_i+1
average.append(avg)
return average
if __name__=="__main__":
lst2013=avg_data_2013()
lst2014=avg_data_2014()
lst2015=avg_data_2015()
lst2016=avg_data_2016()
lst2017=avg_data_2017()
lst2018=avg_data_2018()
#FYI optional
#The above code works, although it needs to be written once. there is a repetition. Will work on it, later.
#As when I create a DRY concept, the Extract_combine.py is not loading the variables. (Getting a type error)