python - pandas how to convert all the string value to float -

i want convert string value in pandas dataframe float, , can define short function this, it's not pythonic way that. dataframe looks this:

>>> df = pd.dataframe(np.array([['1', '2', '3'], ['4', '5', '6']])) >>> df    0  1  2 0  1  2  3 1  4  5  6 >>> df.dtypes 0    object 1    object 2    object dtype: object >>> type(df[0][0]) <type 'str'> 

i wonder whether there built-in functions of pandas dataframe convert string value float. if know built-in function on pandas doc, please post link.

assuming values can correctly converted float, can use dataframe.astype() function convert type of complete dataframe float. example -

df = df.astype(float) 

demo -

in [5]: df = pd.dataframe(np.array([['1', '2', '3'], ['4', '5', '6']]))  in [6]: df.astype(float) out[6]:    0  1  2 0  1  2  3 1  4  5  6  in [7]: df = df.astype(float)  in [8]: df.dtypes out[8]: 0    float64 1    float64 2    float64 dtype: object 

.astype() function has raise_on_error argument (which defaults true) can set false make ignore errors . in such cases, original value used in dataframe -

in [10]: df = pd.dataframe([['1', '2', '3'], ['4', '5', '6'],['blah','bloh','bleh']])  in [11]: df.astype(float,raise_on_error=false) out[11]:       0     1     2 0     1     2     3 1     4     5     6 2  blah  bloh  bleh 

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to convert series/column float, again assuming values can converted, can use [series.astype()][2] . example -

df['somecol'] = df['somecol'].astype(<type>)