サマータイムが1時間シフトしたときに誤ってインデックスを再作成する

Question

米国の夏時間タイムゾーンで発生する1時間のタイムシフトを解決しようとしています。私が使用して、新しい日付範囲に適用する場合、時系列の一部の

この

現在

In [3] eurusd 
    Out[3]: 
         BID-CLOSE 
    TIME       
    1994-03-28 22:00:00 1.15981 
    1994-03-29 22:00:00 1.16681 
    1994-03-30 22:00:00 1.15021 
    1994-03-31 22:00:00 1.14851 
    1994-04-03 21:00:00 1.14081 
    1994-04-04 21:00:00 1.13921 
    1994-04-05 21:00:00 1.13881 
    1994-04-06 21:00:00 1.14351 
    1994-04-07 21:00:00 1.14411 
    1994-04-10 21:00:00 1.14011 
    1994-04-11 21:00:00 1.14391 
    1994-04-12 21:00:00 1.14451 
    1994-04-13 21:00:00 1.14201 
    1994-04-14 21:00:00 1.13911 
    1994-04-17 21:00:00 1.14821 
    1994-04-18 21:00:00 1.15181 
    1994-04-19 21:00:00 1.15621 
    1994-04-20 21:00:00 1.15381 
    1994-04-21 21:00:00 1.16201 
    1994-04-24 21:00:00 1.16251 
    1994-04-25 21:00:00 1.16721 
    1994-04-26 21:00:00 1.17101 
    1994-04-27 21:00:00 1.17721 
    1994-04-28 21:00:00 1.18421 
    1994-05-01 21:00:00 1.18751 
    1994-05-02 21:00:00 1.17331 
    1994-05-03 21:00:00 1.16801 
    1994-05-04 21:00:00 1.17141 
    1994-05-05 21:00:00 1.17691 
    1994-05-08 21:00:00 1.16541 
          ... 
    1994-09-26 21:00:00 1.25501 
    1994-09-27 21:00:00 1.25761 
    1994-09-28 21:00:00 1.25541 
    1994-09-29 21:00:00 1.25421 
    1994-10-02 21:00:00 1.25721 
    1994-10-03 21:00:00 1.26131 
    1994-10-04 21:00:00 1.26121 
    1994-10-05 21:00:00 1.26101 
    1994-10-06 21:00:00 1.25761 
    1994-10-10 21:00:00 1.26161 
    1994-10-11 21:00:00 1.26341 
    1994-10-12 21:00:00 1.27821 
    1994-10-13 21:00:00 1.29411 
    1994-10-16 21:00:00 1.29401 
    1994-10-17 21:00:00 1.29371 
    1994-10-18 21:00:00 1.29531 
    1994-10-19 21:00:00 1.29681 
    1994-10-20 21:00:00 1.29971 
    1994-10-23 21:00:00 1.30411 
    1994-10-24 21:00:00 1.30311 
    1994-10-25 21:00:00 1.30091 
    1994-10-26 21:00:00 1.28921 
    1994-10-27 21:00:00 1.29341 
    1994-10-30 22:00:00 1.29931 
    1994-10-31 22:00:00 1.29281 
    1994-11-01 22:00:00 1.27771 
    1994-11-02 22:00:00 1.27821 
    1994-11-03 22:00:00 1.28321 
    1994-11-06 22:00:00 1.28751 
    1994-11-07 22:00:00 1.27091 

（以下つむ）：次に

idx = pd.date_range('1994-03-28 22:00:00', '1994-11-07 22:00:00', freq= 'D') 

In [4] idx 
Out[4]: 
DatetimeIndex(['1994-03-28 22:00:00', '1994-03-29 22:00:00', 
       '1994-03-30 22:00:00', '1994-03-31 22:00:00', 
       '1994-04-01 22:00:00', '1994-04-02 22:00:00', 
       '1994-04-03 22:00:00', '1994-04-04 22:00:00', 
       '1994-04-05 22:00:00', '1994-04-06 22:00:00', 
       ... 
       '1994-10-29 22:00:00', '1994-10-30 22:00:00', 
       '1994-10-31 22:00:00', '1994-11-01 22:00:00', 
       '1994-11-02 22:00:00', '1994-11-03 22:00:00', 
       '1994-11-04 22:00:00', '1994-11-05 22:00:00', 
       '1994-11-06 22:00:00', '1994-11-07 22:00:00'], 
       dtype='datetime64[ns]', length=225, freq='D') 

を、私は新しい日付範囲を使用してデータフレームのインデックスを再作成しますtimeseriesはすべての21:00の値を22:00に変換し、BID-CLOSEはNaNになります。なぜ私は、米国夏時間スケジュールに従ってコードを1時間のステップに気づかせるのかがわかりません。 REINDEXの

出力：

In[5]: eurusd_copy1 = eurusd.reindex(idx, fill_value=None) 

In[6]: eurusd_copy1 
Out[6]: 
        BID-CLOSE 
1994-03-28 22:00:00 1.15981 
1994-03-29 22:00:00 1.16681 
1994-03-30 22:00:00 1.15021 
1994-03-31 22:00:00 1.14851 
1994-04-01 22:00:00  NaN 
1994-04-02 22:00:00  NaN 
1994-04-03 22:00:00  NaN 
1994-04-04 22:00:00  NaN 
1994-04-05 22:00:00  NaN 
1994-04-06 22:00:00  NaN 
1994-04-07 22:00:00  NaN 
1994-04-08 22:00:00  NaN 
1994-04-09 22:00:00  NaN 
1994-04-10 22:00:00  NaN 
1994-04-11 22:00:00  NaN 
1994-04-12 22:00:00  NaN 
1994-04-13 22:00:00  NaN 
1994-04-14 22:00:00  NaN 
1994-04-15 22:00:00  NaN 
1994-04-16 22:00:00  NaN 
1994-04-17 22:00:00  NaN 
1994-04-18 22:00:00  NaN 
1994-04-19 22:00:00  NaN 
1994-04-20 22:00:00  NaN 
1994-04-21 22:00:00  NaN 
1994-04-22 22:00:00  NaN 
1994-04-23 22:00:00  NaN 
1994-04-24 22:00:00  NaN 
1994-04-25 22:00:00  NaN 
1994-04-26 22:00:00  NaN 
         ... 
1994-10-09 22:00:00  NaN 
1994-10-10 22:00:00  NaN 
1994-10-11 22:00:00  NaN 
1994-10-12 22:00:00  NaN 
1994-10-13 22:00:00  NaN 
1994-10-14 22:00:00  NaN 
1994-10-15 22:00:00  NaN 
1994-10-16 22:00:00  NaN 
1994-10-17 22:00:00  NaN 
1994-10-18 22:00:00  NaN 
1994-10-19 22:00:00  NaN 
1994-10-20 22:00:00  NaN 
1994-10-21 22:00:00  NaN 
1994-10-22 22:00:00  NaN 
1994-10-23 22:00:00  NaN 
1994-10-24 22:00:00  NaN 
1994-10-25 22:00:00  NaN 
1994-10-26 22:00:00  NaN 
1994-10-27 22:00:00  NaN 
1994-10-28 22:00:00  NaN 
1994-10-29 22:00:00  NaN 
1994-10-30 22:00:00 1.29931 
1994-10-31 22:00:00 1.29281 
1994-11-01 22:00:00 1.27771 
1994-11-02 22:00:00 1.27821 
1994-11-03 22:00:00 1.28321 
1994-11-04 22:00:00  NaN 
1994-11-05 22:00:00  NaN 
1994-11-06 22:00:00 1.28751 
1994-11-07 22:00:00 1.27091 

[225 rows x 1 columns] 

所望の出力は、しかし、既に日付がunchnagedたBID-近い値を保つは、NaNを充填した任意の日付ギャップを有するであろう。以下の出力は架空のもので、目的の結果を説明するだけです。

     BID-CLOSE 
28/03/1994 22:00:00 1.15981 
29/03/1994 22:00:00 1.16681 
30/03/1994 22:00:00 1.15021 
31/03/1994 22:00:00 1.14851 
01/04/1994 21:00:00  NaN 
02/04/1994 21:00:00  NaN 
03/04/1994 21:00:00 1.13881 
04/04/1994 21:00:00 1.14351 
05/04/1994 21:00:00 1.14411 
06/04/1994 21:00:00 1.14011 
07/04/1994 21:00:00 1.14391 
08/04/1994 21:00:00  NaN 
09/04/1994 21:00:00  NaN 
10/04/1994 21:00:00 1.14451 
11/04/1994 21:00:00 1.14201 
12/04/1994 21:00:00 1.13911 
13/04/1994 21:00:00 1.14821 
     …  
25/10/1994 21:00:00 1.29371 
26/10/1994 21:00:00  NaN 
27/10/1994 21:00:00 1.29681 
28/10/1994 21:00:00 1.29971 
29/10/1994 21:00:00 1.30411 
30/10/1994 22:00:00 1.30311 
31/10/1994 22:00:00  NaN 
01/11/1994 22:00:00  NaN 
02/11/1994 22:00:00 1.29341 

コードで米国時間帯を認識できるようにするにはどうすればよいですか？

Answer 1

あなたの日付インデックスがタイムゾーンが未知であると推測しています。

が最初にタイムゾーンを設定し、私は彼らがUTC

eurusd = eurusd.tz_localize('UTC') 

あると仮定します、あなたは、あなたがそのようなものが

eurusd = eurusd.tz_convert('America/New_York') 

を持っているように、あなたのように、インデックスを再可能性がどのような時間帯に変換することができますあなたは好きです