python - Replace a variable number of asterisks with NaN in a dataframe -


i'm trying scrub climate data ncdc , has columns varying number of asterisks indicate empty fields. want replace np.nan.

i have tried df.replace struggling regex syntax handle variable length of asterisks in field. suspect need df.replace('?', np.nan) '?' regex match number of asterisks.

here clip of data:

usaf    wban    yr--modahrmn    dir     spd     gus     clg     skc     l   m   ...     slp     alt     stp     max     min     pcp01   pcp06   pcp24   pcpxx   sd 0   722543  12977   200601010053    160     6   ***     722     clr     *   *   ...     1010.9  29.83   1007.2  ***     ***     0.00    *****   *****   *****   ** 1   722543  12977   200601010153    160     9   ***     722     clr     *   *   ...     1011.0  29.83   1007.2  ***     ***     0.00    *****   *****   *****   ** 2   722543  12977   200601010253    160     9   ***     722     clr     *   *   ...     1011.1  29.83   1007.2  ***     ***     0.00    *****   *****   *****   ** 3   722543  12977   200601010313    160     10  ***     722     sct     *   *   ...     ******  29.83   1007.2  ***     ***     *****   *****   *****   *****   ** 4   722543  12977   200601010321    160     10  ***     4       bkn     *   *   ...     ******  29.83   1007.2  ***     ***     *****   *****   *****   *****   **

df.replace regex pattern '^\*+$' works enough this:

in [790]: df.replace('^\*+$', np.nan, regex=true) out[790]:       usaf   wban  yr--modahrmn  dir  spd  gus  clg  skc   l   m     slp  \ 0  722543  12977  200601010053  160    6  nan  722  clr nan nan  1010.9    1  722543  12977  200601010153  160    9  nan  722  clr nan nan  1011.0    2  722543  12977  200601010253  160    9  nan  722  clr nan nan  1011.1    3  722543  12977  200601010313  160   10  nan  722  sct nan nan     nan          alt     stp  max  min pcp01  pcp06  pcp24  pcpxx  sd   0  29.83  1007.2  nan  nan  0.00    nan    nan    nan nan   1  29.83  1007.2  nan  nan  0.00    nan    nan    nan nan   2  29.83  1007.2  nan  nan  0.00    nan    nan    nan nan   3  29.83  1007.2  nan  nan   nan    nan    nan    nan nan

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