diff --git a/ex1 b/ex1
new file mode 100644
index 0000000..3c2b3a1
--- /dev/null
+++ b/ex1
@@ -0,0 +1 @@
+print(sum([x for x in range(1,1000) if ((x%5==0) or (x%3==0))]))
diff --git a/ex2 b/ex2
new file mode 100644
index 0000000..c2370cb
--- /dev/null
+++ b/ex2
@@ -0,0 +1,21 @@
+#Cada término en la serie de Fibonacci es generado a partir de la suma de los dos términos previos, empezando de 1 y 2, los diez primeros #términos serán: 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, … Considerando los términos de la serie de Fibonacci que son impares, y por debajo de un #millón encuentre la suma de dichos términos.
+
+
+def fib(n):
+  f=[1,2]
+  if n==1:
+   return f[0]
+  if n==2:
+   return [1,2]
+
+  for k in range(3,n+1):
+   f.append(f[k-2]+f[k-3])
+  return f
+
+for i in range(3,40):
+ if fib(i)[-1]>1000000:
+  lim=i
+  break
+
+print(sum([x for x in fib(lim-1) if x%2==1]))
+print(fib(30))
diff --git a/ex3 b/ex3
new file mode 100644
index 0000000..9f08b3e
--- /dev/null
+++ b/ex3
@@ -0,0 +1,10 @@
+def prim_factors(n):
+  factors=[]
+  for i in range(2,n):
+   if (n%i==0):
+    n=n//i
+    factors.append(i)
+  
+  return factors # [x for x in factors if prim_factors(x)==[]]
+
+print(prim_factors(600851475143))
diff --git a/ex3.py b/ex3.py
new file mode 100644
index 0000000..208678a
--- /dev/null
+++ b/ex3.py
@@ -0,0 +1,15 @@
+def prime_factors(n):
+  factors=[]
+  i=2
+  while i*i<=n:
+   #print(i,n)
+   if (n%i==0):
+    n=n//i
+    factors.append(i)
+    i=2
+   else:
+    i+=1
+  factors.append(n) 
+  return sorted(list(set(factors)))[-1]
+
+print(prime_factors(600851475143))
diff --git a/ex4.py b/ex4.py
new file mode 100644
index 0000000..15f1fff
--- /dev/null
+++ b/ex4.py
@@ -0,0 +1,16 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+data=np.loadtxt('lista.txt',delimiter=' ')
+x=data.T[0]
+y=data.T[1]
+
+
+plt.scatter(x,y)
+plt.xlabel('Eje x')
+plt.ylabel('Eje y')
+for i, txt in enumerate(zip(x,y)):
+    plt.annotate(txt, (x[i], y[i]))
+plt.show()
+
diff --git a/ex6.py b/ex6.py
new file mode 100644
index 0000000..1cc9f18
--- /dev/null
+++ b/ex6.py
@@ -0,0 +1,32 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.optimize import curve_fit
+
+def fitFunc(t, a, b, c):
+    return a*t**2+b*t+c
+
+data=np.loadtxt('lista.txt',delimiter=' ')
+t=data.T[0]
+y=data.T[1]
+
+
+fitParams, fitCovariances = curve_fit(fitFunc, t, y)
+print(fitParams)
+print(fitCovariances)
+
+plt.ylabel('Temperature (C)', fontsize = 16)
+plt.xlabel('time (s)', fontsize = 16)
+#plt.xlim(0,4.1)
+# plot the data as red circles with errorbars in the vertical direction
+plt.errorbar(t, y, fmt = 'ro', yerr = 0.2)
+# now plot the best fit curve and also +- 3 sigma curves
+# the square root of the diagonal covariance matrix element 
+# is the uncertianty on the corresponding fit parameter.
+sigma = [fitCovariances[0,0], fitCovariances[1,1], fitCovariances[2,2] ]
+plt.plot(t, fitFunc(t, fitParams[0], fitParams[1], fitParams[2]),\
+         t, fitFunc(t, fitParams[0] + sigma[0], fitParams[1] - sigma[1], fitParams[2] + sigma[2]),\
+         t, fitFunc(t, fitParams[0] - sigma[0], fitParams[1] + sigma[1], fitParams[2] - sigma[2])\
+         )
+plt.show()
+# save plot to a file
+#savefig('dataFitted.pdf', bbox_inches=0, dpi=600)
diff --git a/ex7.py b/ex7.py
new file mode 100644
index 0000000..f4ce0e0
--- /dev/null
+++ b/ex7.py
@@ -0,0 +1,29 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+def pol(x):
+  return x**3+x**2-4*x+4
+
+#def der(x):
+#  return 3*x**2+2*x-4
+
+
+x=np.arange(-10,10,0.1)
+y=[pol(t) for t in x]
+z= np.diff(y)
+print(z)
+plt.plot(x,y)
+plt.plot(x,z,color='red')
+plt.xlabel('Eje x')
+plt.ylabel('Eje y')
+plt.grid()
+plt.legend(['Polinomio','Derivada'])
+plt.show()
+
+print(np.c_[x, y].shape)
+#with open('pol_data.txt','w') as file:
+file= open('pol_data.txt','w')
+np.savetxt(file, np.c_[x, y], fmt='%f', delimiter='\t', header="x #f(x)")
+
+file.close()
+
diff --git a/lista.txt b/lista.txt
new file mode 100644
index 0000000..57c72b6
--- /dev/null
+++ b/lista.txt
@@ -0,0 +1,10 @@
+7.5 	28.66
+4.48 	20.37
+8.60 	22.33
+7.73 	26.35
+5.28 	22.29
+4.25 	21.74
+6.99 	23.11
+6.31 	23.13
+9.15 	24.68
+5.06 	21.89