如何将具有日期时间索引的 Pandas 数据框按日期分组，将属于日期的值拆分为多列？

Question

Consider a dataframe:

  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

I want to transform in to:

 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

How can this be done?

I tried pd.groupby with Grouper and then doing a for loop like below:

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

No luck!

Answer 1

Let's try with 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