How do I change the scale size of my scatter points with values based on a column?

So, I have the following plot, which is a map I’m projecting for my work, I have the data of mean frequency which is plotted and the size must vary within the hv_mean_freq values, but even though I think its happening, the sizes are too small to visualize, how can I change that? So they still follow the sizes of the values given but on a larger scale?

ax = fig.add_subplot()
plt.axis([-50.05,-49.4, -13.3, -12.62])
aguabonita = bacia_aguiar.plot(ax=ax, figsize=(25, 15), color='#FFE5AC')

vereda_verde.plot(ax=aguabonita, color='#F3A773', label='Fm. Vereda Verde')
bacia_aguiar.boundary.plot(ax=ax, color='Brown', linewidth=1, label='Bacia segundo Aguiar(2013)')
bacia.boundary.plot(ax=aguabonita, color="#7814F9",linewidth=1, label='Bacia segundo CPRM(2016)' )
lineamento.plot(ax=aguabonita, color='#461706', linewidth=.9, LineStyle='--', label='Lineamentos' )

rodovia_TO.plot(ax=aguabonita,color="#CA9222", linewidth=2, alpha=.4, label='Rodovias')
hidrografia.plot(ax=aguabonita, color="LightBlue", linewidth=1.5, label="CorposD'água")
hidrografia_02.plot(ax=aguabonita, color="LightBlue", linewidth=1.5)
limites.boundary.plot(ax=aguabonita, color="Gray",linewidth=.7, label='Limite Estadual')
sre.plot(ax=aguabonita, color="#CA9222", linewidth=2, alpha=.4)




####### Municípios
ax.text(-49.83, -12.92, "Araguaçu", transform=ax.transData, fontsize="14")
ax.text(-49.59, -12.98, "Marilândia", transform=ax.transData)
ax.text(-49.97, -13.08, "Tataíra", transform=ax.transData)
ax.text(-49.50, -13.24, "Novo Planalto", transform=ax.transData, fontsize="14")
ax.text(-50.02, -12.75, "Baianópolis", transform=ax.transData)
ax.text(-49.55, -13.22, "GO", transform=ax.transData, rotation=-35, fontsize="24", alpha=0.3, color="Gray")
ax.text(-49.53, -13.19, "TO", transform=ax.transData, rotation=-35, fontsize="24", alpha=0.3, color="Gray")

plt.legend(loc="upper left")
plt.yticks(rotation = 90)


###scatter plots of results
s=hvsrperfil_04.hv_mean_f0_fr_
plt.scatter(hvsrperfil_04.Longitude, hvsrperfil_04.Latitude,c=s, s=s, cmap='inferno', label='HVSR Mean F0 Frequencies') # not sure of your x, y
plt.colorbar()


####### Norte
x, y, arrow_length = 0.95, 0.99, 0.1
ax.annotate('N', xy=(x, y), xytext=(x, y-arrow_length),
            arrowprops=dict(facecolor='black', width=5, headwidth=25),
            ha='center', va='center', fontsize=20,
            xycoords=ax.transAxes)

####### Escala Gráfica
df = aguabonita
A=[-49.5*np.pi/180.,-12.7*np.pi/180.] #Latitude of interest here 40.7 deg, longitude -74.5
B=[-50.5*np.pi/180.,-12.7*np.pi/180.] ##Latitude of interest here 40.7 deg, longitude -74.5+1
dx=(6371000)*haversine_distances([A,B])[0,1]
ax.add_artist(ScaleBar(dx=dx,units="m", location="lower center")) 

>Solution :

You can to use a multiplication factor. For example, instead of using s=s in matplotlib scatter function, you can use s=10*s or even s=100*s.

Because i suppose they are just very small: