- API reference
- DataFrame
- pandas.DataF...
pandas.DataFrame.from_records#
- classmethodDataFrame.from_records(data,index=None,exclude=None,columns=None,coerce_float=False,nrows=None)[source]#
Convert structured or record ndarray to DataFrame.
Creates a DataFrame object from a structured ndarray, sequence oftuples or dicts, or DataFrame.
- Parameters:
- datastructured ndarray, sequence of tuples or dicts, or DataFrame
Structured input data.
Deprecated since version 2.1.0:Passing a DataFrame is deprecated.
- indexstr, list of fields, array-like
Field of array to use as the index, alternately a specific set ofinput labels to use.
- excludesequence, default None
Columns or fields to exclude.
- columnssequence, default None
Column names to use. If the passed data do not have namesassociated with them, this argument provides names for thecolumns. Otherwise this argument indicates the order of the columnsin the result (any names not found in the data will become all-NAcolumns).
- coerce_floatbool, default False
Attempt to convert values of non-string, non-numeric objects (likedecimal.Decimal) to floating point, useful for SQL result sets.
- nrowsint, default None
Number of rows to read if data is an iterator.
- Returns:
- DataFrame
See also
DataFrame.from_dictDataFrame from dict of array-like or dicts.
DataFrameDataFrame object creation using constructor.
Examples
Data can be provided as a structured ndarray:
>>>data=np.array([(3,'a'),(2,'b'),(1,'c'),(0,'d')],...dtype=[('col_1','i4'),('col_2','U1')])>>>pd.DataFrame.from_records(data) col_1 col_20 3 a1 2 b2 1 c3 0 d
Data can be provided as a list of dicts:
>>>data=[{'col_1':3,'col_2':'a'},...{'col_1':2,'col_2':'b'},...{'col_1':1,'col_2':'c'},...{'col_1':0,'col_2':'d'}]>>>pd.DataFrame.from_records(data) col_1 col_20 3 a1 2 b2 1 c3 0 d
Data can be provided as a list of tuples with corresponding columns:
>>>data=[(3,'a'),(2,'b'),(1,'c'),(0,'d')]>>>pd.DataFrame.from_records(data,columns=['col_1','col_2']) col_1 col_20 3 a1 2 b2 1 c3 0 d