pandas.read_csv(filepath, delimiter=None, names=None)

We usually use read_csv() to read a csv file and turn it into dataframe. It is a very useful function. Sometimes we face the problem that the file has not a header and the first line will be the column names of the dataframe. To solve this problem, you can add your expected column names to "names" in the form of names = \['a', 'b', 'c'\]. 

Some times there are rows with exceptional column numbers. For example, 4 are needed but this row have 5. Thus, some error will stop the program. To solve this, you can set \[error_bad_lines = False\] to drop those lines.

pd.read_csv()

pd.concat([s1, s2])

We should notice that the default if to concat by index, which means you will have more rows after this operation. If you want to concat by columns, set axis = 1.

pd.concat()

These are two function of pandas dataframe which makes people confuse sometimes. Actually there is no difference in use between these two functions!

pd.isna() & pd.isnull()

how = ‘left’, ‘right’, ‘outer’, ‘inner’, ‘cross’

The former four are usually used. The concept of them are shown in the graph. Since cross join is difficult to be applied as the dataframe is big, it is seldom used.

pd.merge()

unique() is often used to find the unique elements. It usually returns an array. 

unique().tolist() can store the elements into a list.

len(unique()) can find how many unique elements there are.

pd.unique()

There are three sorting methods in pandas. 

* By rows: pd.sort_index()
* By columns: pd.sort_index(axis = 1)
* By values: pd.sort_values(by = 'col')

To change the order, set "ascending = False"

Sorting in pandas

The frequently asked problems about pandas useful functions can be shared here.

University of Michigan - Ann Arbor

All references relating to the pandas library of Python.

Pandas References

https://pandas.pydata.org/docs/index.html

Pandas documentation

• Working with pandas DataFrames in Python https://www.datacamp.com/community/tutorials/pandas-tutorial-dataframe-python

• Article on tips and tricks to save time when using pandas library https://www.dataschool.io/python-pandas-tips-and-tricks/

• An interactive tutorial website about pandas 
https://www.learnpython.org/en/Pandas_Basics

Pandas Website References

• Data analysis in python with pandas YouTube video series https://www.youtube.com/playlist?list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y

Pandas Video References

Pandas useful functions

Reference: https://stackabuse.com/beginners-tutorial-on-the-pandas-python-library/#:~:text=Advantages%20of%20Using%20Pandas&text=It%20can%20present%20data%20in,operations%20in%20a%20seamless%20manner.

Beginner's Tutorial on the Pandas Python Library

https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html

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