如何將具有日期時間索引的 Pandas 數據框按日期分組，將屬於日期的值拆分為多列？

Question

考慮一個數據框：

  timestamp                                       value
0 2019-07-12 18:00:00                             8.46
1 2019-07-13 06:00:00                            12.02
2 2019-07-13 18:00:00                            15.58
3 2019-07-14 06:00:00                            16.29
4 2019-07-14 18:00:00                            17.00

我想轉變為：

 timestamp                               X1       X2
0 2019-07-12                             8.46     NaN
1 2019-07-13                             12.02    15.58
2 2019-07-14                             16.29    17.00

如何才能做到這一點？

我用Grouper嘗試了pd.groupby ，然后執行如下 for 循環：

for ix, i in resampled_df.groupby(pd.Grouper(key='timestamp', freq="1D")):
    print(i.head())

沒有運氣！

Answer 1

讓我們嘗試使用pivot_table ：

# Convert to datetime (if not already)
df['timestamp'] = pd.to_datetime(df['timestamp'])
# Get Series of Dates from Timestamp
dates = df['timestamp'].dt.date
df = (
    # Pivot on dates in index, and columns based on rows per group
    df.pivot_table(index=dates,
                   columns=df['value'].groupby(dates).cumcount() + 1,
                   values='value')
        .add_prefix('X')  # Add X in Front of Columns
        .reset_index()  # Make dates a column
)

df ：

    timestamp     X1     X2
0  2019-07-12   8.46    NaN
1  2019-07-13  12.02  15.58
2  2019-07-14  16.29  17.00