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##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
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##  Max.   :25.0   Max.   :120.00

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import pandas as pd
df=pd.read_excel("CA_VMP_1.xlsx")
df.info()

## <class 'pandas.core.frame.DataFrame'>
## RangeIndex: 76 entries, 0 to 75
## Data columns (total 46 columns):
##  #   Column    Non-Null Count  Dtype  
## ---  ------    --------------  -----  
##  0   PM10      76 non-null     int64  
##  1   PM10_INC  76 non-null     int64  
##  2   Al        76 non-null     int64  
##  3   Al_INC    76 non-null     int64  
##  4   Ba        76 non-null     int64  
##  5   Ba_INC    76 non-null     float64
##  6   B         76 non-null     float64
##  7   B_INC     76 non-null     float64
##  8   Ca        76 non-null     int64  
##  9   Ca_INC    76 non-null     int64  
##  10  Cd        76 non-null     float64
##  11  Cd_INC    76 non-null     float64
##  12  Cr        76 non-null     float64
##  13  Cr_INC    76 non-null     float64
##  14  Cu        76 non-null     int64  
##  15  Cu_INC    76 non-null     int64  
##  16  Fe        76 non-null     int64  
##  17  Fe_INC    76 non-null     int64  
##  18  K         76 non-null     int64  
##  19  K_INC     76 non-null     int64  
##  20  Mg        76 non-null     int64  
##  21  Mg_INC    76 non-null     int64  
##  22  Mn        76 non-null     int64  
##  23  Mn_INC    76 non-null     float64
##  24  Mo        76 non-null     float64
##  25  Mo_INC    76 non-null     float64
##  26  Na        76 non-null     int64  
##  27  Na_INC    76 non-null     int64  
##  28  Ni        76 non-null     float64
##  29  Ni_INC    76 non-null     float64
##  30  P         76 non-null     float64
##  31  P_INC     76 non-null     float64
##  32  Pb        76 non-null     int64  
##  33  Pb_INC    76 non-null     int64  
##  34  Sb        76 non-null     float64
##  35  Sb_INC    76 non-null     float64
##  36  Si        76 non-null     int64  
##  37  Si_INC    76 non-null     int64  
##  38  Sr        76 non-null     float64
##  39  Sr_INC    76 non-null     float64
##  40  Ti        76 non-null     int64  
##  41  Ti_INC    76 non-null     float64
##  42  V         76 non-null     float64
##  43  V_INC     76 non-null     float64
##  44  Zn        76 non-null     int64  
##  45  Zn_INC    76 non-null     int64  
## dtypes: float64(21), int64(25)
## memory usage: 27.4 KB

Graficos python

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
df.plot("PM10", "PM10_INC", kind="scatter",color='green')

sns.set(color_codes=True)
sns.set_style('white')
sns.displot(df['PM10'], color='g',kde = True)

import plotly.express as px

fig = px.scatter(df, x="PM10", y="Ca", marginal_y="violin",
           marginal_x="box", trendline="ols", template="simple_white")
fig.show()

import plotly.express as px
df = px.data.gapminder()
fig = px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_group="country",
           size="pop", color="continent", hover_name="country", facet_col="continent",
           log_x=True, size_max=45, range_x=[100,100000], range_y=[25,90])
fig.show()