回答編集履歴
2
訂正……
answer
CHANGED
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@@ -24,43 +24,43 @@
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df = pd.read_csv(io.StringIO(text))
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df2 = pd.read_csv(io.StringIO(text2)).fillna(pd.NaT)
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df.iloc[:, 0] = pd.to_datetime(df.iloc[:, 0]).dt.strftime('%Y%
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df.iloc[:, 0] = pd.to_datetime(df.iloc[:, 0]).dt.strftime('%Y%m%d').astype(float)
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df2.iloc[:, 0] = pd.to_datetime(df2.iloc[:, 0]).dt.strftime('%Y%
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df2.iloc[:, 0] = pd.to_datetime(df2.iloc[:, 0]).dt.strftime('%Y%m%d').astype(float)
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df2.iloc[:, 1] = pd.to_datetime(df2.iloc[:, 1]).dt.strftime('%Y%
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df2.iloc[:, 1] = pd.to_datetime(df2.iloc[:, 1]).dt.strftime('%Y%m%d').astype(float)
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df2.iloc[:, 2] = pd.to_datetime(df2.iloc[:, 2]).dt.strftime('%Y%
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df2.iloc[:, 2] = pd.to_datetime(df2.iloc[:, 2]).dt.strftime('%Y%m%d').astype(float)
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print(df)
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-
#
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# birthday
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34
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-
# 12
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34
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# 12 19100101.0
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# 9
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# 9 19800203.0
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# 8
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# 8 19620404.0
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# 10
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# 10 19490406.0
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print(df2)
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# high_school university1 university2
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# 8
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# 8 19770331.0 19850331.0 19990331.0
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# 9
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# 9 19950331.0 NaN NaN
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# 10
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# 10 19540331.0 19640331.0 NaN
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43
43
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```
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45
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として、
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```Python
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result = df2.sub(df['birthday'], 0) //
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result = df2.sub(df['birthday'], 0) // 10000
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print(result.astype('Int64'))
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# high_school university1 university2
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# 8
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# 8 14 22 36
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# 9 15 <NA> <NA>
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# 10
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# 10 4 14 <NA>
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# 12 <NA> <NA> <NA>
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```
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56
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あるいは、
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```Python
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result = df2.sub(df['birthday'].reindex(df2.index), 0) //
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result = df2.sub(df['birthday'].reindex(df2.index), 0) // 10000
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print(result.astype('Int64'))
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# high_school university1 university2
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# 8
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# 8 14 22 36
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# 9 15 <NA> <NA>
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-
# 10
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# 10 4 14 <NA>
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66
66
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```
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1
追記
answer
CHANGED
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@@ -2,4 +2,65 @@
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2
2
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DataFrame2.sub(DataFrame1["birthday"], 0)//pd.Timedelta(365, 'D')
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3
3
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```
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4
4
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5
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---
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6
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7
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追記
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8
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9
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```Python
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10
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import io
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import pandas as pd
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12
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text = """birthday
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14
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12,'1910-01-01'
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9,'1980-02-03'
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8,'1962-04-04'
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10,'1949-04-06'"""
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text2 = """high_school,university1,university2
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8,'1977-03-31','1985-03-31','1999-3-31'
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9,'1995-03-31',,
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10,'1954-03-31','1964-3-31',
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"""
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23
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df = pd.read_csv(io.StringIO(text))
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df2 = pd.read_csv(io.StringIO(text2)).fillna(pd.NaT)
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df.iloc[:, 0] = pd.to_datetime(df.iloc[:, 0]).dt.strftime('%Y%M').astype(float)
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df2.iloc[:, 0] = pd.to_datetime(df2.iloc[:, 0]).dt.strftime('%Y%M').astype(float)
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df2.iloc[:, 1] = pd.to_datetime(df2.iloc[:, 1]).dt.strftime('%Y%M').astype(float)
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df2.iloc[:, 2] = pd.to_datetime(df2.iloc[:, 2]).dt.strftime('%Y%M').astype(float)
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31
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print(df)
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33
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# birthday
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34
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# 12 191000.0
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# 9 198000.0
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# 8 196200.0
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# 10 194900.0
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5
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-
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print(df2)
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# high_school university1 university2
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40
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# 8 197700.0 198500.0 199900.0
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# 9 199500.0 NaN NaN
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# 10 195400.0 196400.0 NaN
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43
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```
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44
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45
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として、
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46
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47
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```Python
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48
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result = df2.sub(df['birthday'], 0) // 100
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49
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print(result.astype('Int64'))
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50
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# high_school university1 university2
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# 8 15 23 37
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# 9 15 <NA> <NA>
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53
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# 10 5 15 <NA>
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54
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# 12 <NA> <NA> <NA>
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55
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```
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56
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+
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57
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あるいは、
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58
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59
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```Python
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60
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result = df2.sub(df['birthday'].reindex(df2.index), 0) // 100
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61
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print(result.astype('Int64'))
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62
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# high_school university1 university2
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63
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# 8 15 23 37
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64
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# 9 15 <NA> <NA>
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65
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# 10 5 15 <NA>
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66
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```
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