Is there any way to check for missing dates in a dataframe directly. I want to check if there are a missing dates between 2013-01-19 to 2018-01-29
            GWA_BTC      GWA_ETH    GWA_LTC  GWA_XLM  GWA_XRP    Date                  2013-01-19  11,826.36   1,068.45    195.00    0.51    1.82 2013-01-20  13,062.68   1,158.71    207.58    0.52    1.75    ... 2018-01-28  12,326.23   1,108.90    197.36    0.48    1.55 2018-01-29  11,397.52   1,038.21    184.92    0.47    1.43   I tried to check it manually but it took a lot of time.
To add missing dates to Python Pandas DataFrame, we can use the DatetimeIndex instance's reindex method. We create a date range index with idx = pd. date_range('09-01-2020', '09-30-2020') .
In order to check missing values in Pandas DataFrame, we use a function isnull() and notnull(). Both function help in checking whether a value is NaN or not. These function can also be used in Pandas Series in order to find null values in a series.
You can use DatetimeIndex.difference(other)
pd.date_range(start = '2013-01-19', end = '2018-01-29' ).difference(df.index)   It returns the elements not present in the other
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