Python Pandas--DataFrame

Pandas. DataFrame

pandas. class DataFrame ( data=none, index=none, columns=none, dtype=none, copy=false) [Source]

Two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can is thought of as a dict-like container for Series objects. The primary pandas data structure

Parameters:

data : NumPy ndarray (structured or homogeneous), dict, or DataFrame Dict can contain Series, arrays, constants, or List-like objects index : index or Array-like Index to use for resulting frame. Would default to Np.arange (n) If no indexing information part of input data and no index provided columns : Index or Array-like Column labels to use for resulting frame. Would default to Np.arange (n) If no column labels is provided dtype : dtype, default None Data type to force. Only a single dtype is allowed. If None, infer Copy : boolean, default False Copy data from inputs. Only affects dataframe/2d Ndarray input

See Also

DataFrame.from_records

constructor from tuples, also record arrays

DataFrame.from_dict

From Dicts of Series, arrays, or dicts

DataFrame.from_items

From

sequence of (key, value) pairs

pandas.read_csv, pandas.read_table,pandas.read_clipboard

1. Start with a side dish.

Create based on dictionary

 fromPandasImportSeries, DataFrameImportPandas as PDImportNumPy as NPD= {'col1': [+],'col2': [3,4]}DF= PD. DataFrame (data=d)Print(DF)Print(df.dtypes)#col1 col2#0 1 3#1 2 4#col1 Int64#col2 Int64#Dtype:object

Ndarrary based on the Numy

DF2 = PD. DataFrame (Np.random.randint (low=0, high=10, Size= (5, 5)), columns=['a','b','C','D','e'])Print(DF2)#a b c d e#0 0 2 4 7 0#1 6 7 3 4 1#2 5 3 3 8 7#3 0 9 4 3 4#4 7 4 7 0 0

Python Pandas--DataFrame