Starting out with Python Pandas DataFrames
The Pandas DataFrame – loading, editing, and viewing data in Python
1. head(), tail()
is it possible mid data, not head or tail?
df.iloc[[row_start:row_end],[column_start:column_end]]
2. describe()
separate data each type, and then use the describe() function
3. selecting column
df.column_name
df['column_name']
df.iloc[:,
4. selecting row
df.iloc[0:10, :] - select data first 10 rows.
df.loc[44, :]
df[df["Area"] == "Ireland"] – select the rows where Area value is ‘Ireland’.
5. From DataFrame to list values
df.column_name.values
df.column_name.tolist()
6. Some columns data
new = old[['A', 'C', 'D']].copy()
new = old.filter(['A', 'C', 'D'], axis=1)
Extracting specific selected columns from a DataFrame to new DataFrame
* remove column
new = old.drop('B', axis=1)
7. Change, update index
df.index = [list_value]
Visualization
Pandas DataFrame Visualization
Data Visualization & Exploration using Pandas Only: Beginner
Modern Pandas (Part 6): Visualization
Visualization with Seaborn
Visualize data with Pandas
Errorbar or box plot, Histogram
Box plot with min, max, average and standard deviation
Python Histograms, Box Plots, & Distributions
Scattering graph
draw box plot & draw all real value (point)
Matplotlib: avoiding overlapping datapoints in a “scatter/dot/beeswarm” plot
Seaborn
DataFrame plot
Understand df.plot in pandas
Data Frames and Plotting
Plotting Series and DataFrame objects
Others
Creating Pandas DataFrames from Lists and Dictionaries
Python에서 데이터 시각화하는 다양한 방법
Create multiple dataframes in loop
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