質問編集履歴
2
取り扱っているファイルについて説明
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -183,3 +183,13 @@
|
|
|
183
183
|
utc_dt = local_dt.astimezone(pytz.utc)
|
|
184
184
|
|
|
185
185
|
```
|
|
186
|
+
|
|
187
|
+
|
|
188
|
+
|
|
189
|
+
### 加工しようとしているファイル
|
|
190
|
+
|
|
191
|
+
上のコードだけではファイルの中身がわからないと思うので、詳細をお伝えします。
|
|
192
|
+
|
|
193
|
+
取り扱おうとしているファイルはルイジアナの日照データなのですが、[こちら](https://midcdmz.nrel.gov/apps/daily.pl?site=ULL;live=1)のリンク上にある"All 1-Min Raw Data (ZIP Compressed)"を選択して"submit"を押すとcsvファイルが入手できます
|
|
194
|
+
|
|
195
|
+
今回のコードはこのCSVファイルを加工したものです。
|
1
全てのコードを記入するため
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -24,25 +24,89 @@
|
|
|
24
24
|
|
|
25
25
|
import pandas as pd
|
|
26
26
|
|
|
27
|
+
import numpy as np
|
|
28
|
+
|
|
29
|
+
import matplotlib.pyplot as plt
|
|
30
|
+
|
|
31
|
+
%matplotlib inline
|
|
32
|
+
|
|
27
33
|
import time, datetime, sys, pytz
|
|
34
|
+
|
|
35
|
+
|
|
36
|
+
|
|
37
|
+
gge_product = "NOAA/GOES/16/MCMIPF" #link: https://developers.google.com/earth-engine/datasets/catalog/NOAA_GOES_16_MCMIPF#bands
|
|
38
|
+
|
|
39
|
+
|
|
40
|
+
|
|
41
|
+
inp_files = []
|
|
42
|
+
|
|
43
|
+
inp_files += [pd.read_csv("/content/drive/MyDrive/GOES/20180901-20181231.csv")]
|
|
44
|
+
|
|
45
|
+
#inp_files += [pd.read_csv("/content/drive/MyDrive/GOES/20190101-20191231.csv")]
|
|
46
|
+
|
|
47
|
+
#inp_files += [pd.read_csv("/content/drive/MyDrive/GOES/20200101-20201231.csv")]
|
|
48
|
+
|
|
49
|
+
#inp_files += [pd.read_csv("/content/drive/MyDrive/GOES/20210101-20210315.csv")]
|
|
28
50
|
|
|
29
51
|
|
|
30
52
|
|
|
31
53
|
|
|
32
54
|
|
|
33
|
-
|
|
55
|
+
for i, df_ in enumerate(inp_files):
|
|
34
56
|
|
|
35
|
-
|
|
57
|
+
if i == 0:
|
|
36
58
|
|
|
59
|
+
df = df_
|
|
60
|
+
|
|
61
|
+
else:
|
|
62
|
+
|
|
37
|
-
|
|
63
|
+
df = pd.concat([df, df_])
|
|
38
64
|
|
|
39
65
|
|
|
40
66
|
|
|
41
|
-
|
|
67
|
+
df.insert(df.columns.get_loc("CST")+1, 'Local Time', '')
|
|
42
68
|
|
|
43
|
-
d
|
|
69
|
+
df.insert(df.columns.get_loc("CST")+2, 'UTC Time', '')
|
|
44
70
|
|
|
71
|
+
df.insert(df.columns.get_loc("CST")+3, 'Unixtime', '')
|
|
72
|
+
|
|
73
|
+
|
|
74
|
+
|
|
75
|
+
|
|
76
|
+
|
|
77
|
+
for i, row in df.iterrows():
|
|
78
|
+
|
|
79
|
+
year = int(row['Year']) #2018
|
|
80
|
+
|
|
81
|
+
doy = int(row['DOY']) #244
|
|
82
|
+
|
|
83
|
+
hour = int(np.floor(row['CST']/100)) #0
|
|
84
|
+
|
|
85
|
+
min = int(row['CST']) -100*hour #0
|
|
86
|
+
|
|
87
|
+
|
|
88
|
+
|
|
89
|
+
date = datetime.datetime(year, 1, 1) +datetime.timedelta(days=doy-1, hours=hour, minutes=min )
|
|
90
|
+
|
|
91
|
+
#print(date) #この行を挿入するとエラーが消滅する
|
|
92
|
+
|
|
93
|
+
|
|
94
|
+
|
|
95
|
+
local = pytz.timezone("US/Central")
|
|
96
|
+
|
|
97
|
+
date_local = local.localize(date, is_dst=None)
|
|
98
|
+
|
|
45
|
-
date_utc = date_local.astimezone(pytz.utc)
|
|
99
|
+
date_utc = date_local.astimezone(pytz.utc)
|
|
100
|
+
|
|
101
|
+
unixtime = date_utc.timestamp() # https://www.tutorialspoint.com/How-to-convert-Python-date-to-Unix-timestamp
|
|
102
|
+
|
|
103
|
+
row['Local Time'] = date
|
|
104
|
+
|
|
105
|
+
row['UTC Time'] = date_utc
|
|
106
|
+
|
|
107
|
+
row['Unixtime'] = unixtime
|
|
108
|
+
|
|
109
|
+
df
|
|
46
110
|
|
|
47
111
|
```
|
|
48
112
|
|