回答編集履歴
2
再度修正
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@@ -1,20 +1,21 @@
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以下でいかがでしょうか。
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レスがあったので再度行ってみましたが、こちらではうまくいってます。
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固定長とのことですの再度修正しました。
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```python
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In [1]: import pandas as pd
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In [2]: df3 = pd.DataFrame({'A': ['2019 1 1 0 0', '2019 2 2 1 2', '
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In [2]: df3 = pd.DataFrame({'A': ['2019 1 1 0 0', '2019 2 2 1 2', '201912312359'],
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...: 'B': [12, 22, 32],
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...: 'C': [13, 23, 33]})
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In [3]: df3.
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In [3]: df3.columns=["Time (GMT+9)", "有義波高 (H1/3) (m)", "最高波周期 (Tp) (s)"]
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Out[3]:
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A object
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B int64
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C int64
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dtype: object
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In [4]: df3
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Out[4]:
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Time (GMT+9) 有義波高 (H1/3) (m) 最高波周期 (Tp) (s)
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0 2019 1 1 0 0 12 13
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1 2019 2 2 1 2 22 23
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2 201912312359 32 33
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In [5]: df3.dtypes
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Out[5]:
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@@ -23,29 +24,31 @@
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最高波周期 (Tp) (s) int64
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dtype: object
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In [6]: df3
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Out[6]:
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In [6]: df3["Time (GMT+9)"] = df3["Time (GMT+9)"].str.replace(' ', '0')
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0 2019 1 1 0 0 12 13
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1 2019 2 2 1 2 22 23
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2 2019 12 31 23 59 32 33
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In [7]: df3
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Out[7]:
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Time (GMT+9) 有義波高 (H1/3) (m) 最高波周期 (Tp) (s)
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0 201901010000 12 13
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1 201902020102 22 23
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2 201912312359 32 33
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In [8]: df3['Time (GMT+9)'] = pd.to_datetime(df3['Time (GMT+9)'], format="%Y%m%d%H%M")
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In [
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In [9]: df3
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Out[
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Out[9]:
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Time (GMT+9) 有義波高 (H1/3) (m) 最高波周期 (Tp) (s)
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0 2019-01-01 00:00:00 12 13
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1 2019-02-02 01:02:00 22 23
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2 2019-12-31 23:59:00 32 33
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In [
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In [10]: df3.dtypes
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Out[
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Out[10]:
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Time (GMT+9) datetime64[ns]
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有義波高 (H1/3) (m) int64
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最高波周期 (Tp) (s) int64
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dtype: object
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In [
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In [11]:
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```
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1
修正
answer
CHANGED
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@@ -1,13 +1,51 @@
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1
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-
以下でいかがでしょうか
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1
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+
以下でいかがでしょうか。
|
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2
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+
レスがあったので再度行ってみましたが、こちらではうまくいってます。
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2
3
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```python
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3
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import pandas as pd
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4
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In [1]: import pandas as pd
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4
5
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5
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-
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6
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In [2]: df3 = pd.DataFrame({'A': ['2019 1 1 0 0', '2019 2 2 1 2', '2019 12 31 23 59'],
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...: 'B': [12, 22, 32],
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...: 'C': [13, 23, 33]})
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In [3]: df3.dtypes
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Out[3]:
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12
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A object
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B int64
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14
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C int64
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dtype: object
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# 0 2019-01-01 00:00:00
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# 1 2019-02-02 03:04:00
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In [4]: df3.columns=["Time (GMT+9)", "有義波高 (H1/3) (m)", "最高波周期 (Tp) (s)"]
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In [5]: df3.dtypes
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Out[5]:
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Time (GMT+9) object
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有義波高 (H1/3) (m) int64
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23
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最高波周期 (Tp) (s) int64
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dtype: object
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In [6]: df3
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Out[6]:
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28
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Time (GMT+9) 有義波高 (H1/3) (m) 最高波周期 (Tp) (s)
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29
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0 2019 1 1 0 0 12 13
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1 2019 2 2 1 2 22 23
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2 2019 12 31 23 59 32 33
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32
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In [7]: df3['Time (GMT+9)'] = pd.to_datetime(df3['Time (GMT+9)'], format="%Y %m %d %H %M")
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In [8]: df3
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Out[8]:
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37
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Time (GMT+9) 有義波高 (H1/3) (m) 最高波周期 (Tp) (s)
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38
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0 2019-01-01 00:00:00 12 13
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39
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1 2019-02-02 01:02:00 22 23
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40
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2 2019-12-31 23:59:00 32 33
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41
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In [9]: df3.dtypes
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Out[9]:
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Time (GMT+9) datetime64[ns]
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45
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有義波高 (H1/3) (m) int64
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46
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最高波周期 (Tp) (s) int64
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47
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dtype: object
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48
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49
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In [10]:
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50
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13
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```
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