Shulou(Shulou.com)06/01 Report--

This article mainly shows you "what is the use of pandas in data analysis", the content is easy to understand, clear, hope to help you solve your doubts, the following let the editor lead you to study and learn "what is the use of pandas in data analysis" this article.

Data analysis

The Foundation of python data Science

The basis of machine learning courses

Tools anaconda and jupyter

Matplotlib

View the system font: fc-list: lang=zh

Numpy

NumPy is the basic package for scientific computing using Python.

Official website: https://www.numpy.org.cn/

Pandas

Seres one-dimensional array

T.index

T.values

DataFrame two-dimensional array

Method 1: delete the row and column of NaN dropna (axis=0,how='any',inplace=False)

Processing method 2: populate data t.fillna (t.mean ()) # mean, t.fiall (t.median ()), t.fillna (0)

Data processed as 0: t [tasking 0] = np.nan of course, it is not necessary to calculate the average value every time the data is 0. Nan does not participate in the calculation, but 0 will.

Specify index: t.index = ['x','y']

Reset the index: t.reindex (['x','y'])

Specify a column as the index:t.set_index ("name", drop=False)

Returns the unique value of index: t.set_index ("name") .index.unique ()

Swap the index in levels: t.swaplevel ()

Row index, indicating different rows, horizontal index, called index,0 axis, axis=0

Row index, indicating different columns, vertical index, called columns,1 axis, axis=1

T.index row index

T.columns column index

T.values object value, 2D ndarray array

T.shape shape (rows, columns)

T.dtypes Typ

T.ndim data dimension

T.head (3) displays several lines of the header, with a default of 5 lines

T.tail (3) displays the trailing lines, with a default of 5 lines

Overview of t.info () related information: number of rows, number of columns, column index, number of column non-null values, column type, row type, memory footprint

T.describe () Fast synthesis of statistical results: calculation, mean, standard deviation, maximum, quartile, minimum

T.loc () indexes row data through tags

T.iloc () gets row data by location

Judge whether the data is NaN:pd.isnull (t), pd.notnull (t)

Common statistical methods of pandas

On: specify column

How- > inner (default) intersection merge

Merge in how- > outer union mode, NaN completion

How- > left shall be merged on the left and completed by NaN

How- > right shall be merged on the right, and completed by NaN.

Average: df ["xx"] .mean ()

Maximum: df ["xx"] .max ()

Maximum index: df ["xx"] .idxmax ()

Minimum: df ["xx"] .max ()

Minimum index: df ["xx"] .idxmin ()

Median: df ["xx"] .median ()

Join: the default is to merge data with the same row index together t1.join (T2)

Merge: merges data together in a certain way according to the specified columns t1.merge (T2, on= "a", how= "inner")

Time series.

Ps.to_datetime (df ["timeStamp"])

The above is all the contents of the article "what is the use of pandas in data Analysis". Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.