Refactor code formatting and improve readability in Jupyter notebooks for TP_4 and TP_5

- Adjusted indentation and line breaks for better clarity in function definitions and import statements.
- Standardized string quotes for consistency across the codebase.
- Enhanced readability of DataFrame creation and manipulation by breaking long lines into multiple lines.
- Cleaned up print statements and comments for improved understanding.
- Ensured consistent use of whitespace around operators and after commas.

M1/Numerical Methods/TP_DANJOU_Arthur.ipynb

@@ -159,11 +159,15 @@
     "\n",
     "    for n in range(N - 1):\n",
     "        p1 = f(vt[n], yn[:, n])\n",
+    "\n",
     "        def F1(p2):\n",
     "            return f(vt[n] + h / 3, yn[:, n] + h / 6 * (p1 + p2)) - p2\n",
+    "\n",
     "        p2 = newton(F1, yn[:, n], fprime=None, tol=tol, maxiter=itmax)\n",
+    "\n",
     "        def F2(yn1):\n",
     "            return yn[:, n] + h / 4 * (3 * p2 + f(vt[n + 1], yn1)) - yn1\n",
+    "\n",
     "        yn[:, n + 1] = newton(F2, yn[:, n], fprime=None, tol=tol, maxiter=itmax)\n",
     "    return yn"
    ]