回答編集履歴
2
修正
answer
CHANGED
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@@ -19,13 +19,14 @@
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19
19
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codes = [111,222,333]
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20
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dfs = [get_price(code) for code in codes]
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prices = pd.concat(dfs, axis=1)
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22
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prices.columns = map(str,codes) # 列名を変更
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print(prices)
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"""
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-
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111 222 333
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date
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2019-01-01
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2019-01-01 10.0 NaN NaN
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-
2019-01-02
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2019-01-02 NaN 20.0 NaN
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28
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-
2019-01-03
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2019-01-03 NaN NaN 30.0
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"""
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```
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1
ついでに
answer
CHANGED
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@@ -27,4 +27,30 @@
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27
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2019-01-02 NaN 20.0 NaN
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2019-01-03 NaN NaN 30.0
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"""
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30
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```
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32
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### ついでに
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33
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ふつうに複数の`code`で絞った結果を返したい場合は以下のように書けます。
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34
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```Python
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35
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import sqlite3
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import pandas as pd
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def get_prices(codes):
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con = sqlite3.connect('test.db')
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where = ','.join(map(str,codes)) # codeを直埋め
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sql = 'SELECT date, price FROM prices WHERE code in ({}) ORDER BY date'.format(where)
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print(sql) # SELECT date, price FROM prices WHERE code in (111,222,333) ORDER BY date
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return pd.read_sql(sql, con,
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parse_dates=('date',),
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index_col='date')
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prices = get_prices([111,222,333])
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print(prices)
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"""
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price
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date
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2019-01-01 10
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2019-01-02 20
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2019-01-03 30
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"""
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30
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```
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