Data analysis notes 11

Descriptive analysis

Concentrate on discrete trends
Describe centralized and discrete trends
pandas Realization
Average processing
price_mean = df[“ Unit price ( element / square )”].mean()
Median median()
Numerical method

Image method

Numerical data distribution ： The histogram shows the distribution of data in each interval The histogram shows the change trend of each data
Histogram of x Axes can only be numeric data A histogram is a continuous image distribution y The axis is this section
A histogram is a continuous graphical distribution y The axis is the sum of the numbers in this section The histogram is a single column y The axis is the number corresponding to this value
plt.hist(df[“ Unit price ”])
bins Set the number of intervals Set up 100 A statistical interval More detailed The distribution will be clearer
Normal distribution is the most common distribution state in daily life

numerical analysis

His average The median is equal
Right skewness Median < mean value
Left skewness mean value < Median
Discrete trends Variance and standard deviation
variance .var()
Standard deviation .std()
Standard deviation and variance can better describe which data set is more concentrated A more stable
The quartile A separate quantile() Get the quartile pandas Quartile of describe()