text: import numpy as np
  import matplotlib.pyplot as plt
  import pandas as pd
  #%%
  DAT = pd.read_fwf("table2", header=None)#, dtype="str")
  #%%
  
  DAT.columns = ["0", "1", "2", "3", "intensi", "long", "6", "7", "8", "9", "10", "11", "12", "13", "14"]
  
  DAT
  
  DAT_1 = DAT.apply(pd.to_numeric, errors="coerce")
  DAT_1
  
  type(DAT_1["intensi"][14])
  
  filtrado = DAT_1[DAT_1['intensi'].apply(lambda x: type(x) in [int, np.int64, float, np.float64])]
  #DAT
  #filtrado
  #%%
  
  fig = plt.figure(figsize = (15,15))
  
  plt.scatter(DAT_1["long"], DAT_1["intensi"], s=10)
  plt.show()
  
  #%%
  
  LAMB = pd.read_fwf("Nave_wavelengths.txt", sikprows=9)#, dtype="str")
  
  LAMB.columns = ["Wavelengths"]
  
  long_nave = np.array(LAMB["Wavelengths"][3:]).astype(np.float)
  
  long_nave
  
  mag = np.ones(len(long_nave))
  
  np.savetxt("lineas_NAVE.txt",long_nave)
  
  #%%
  
  fig = plt.figure(figsize = (10,10))
  
  lim_inf = 5400
  lim_sup = 5500
  
  plt.scatter(long_nave, mag, marker="|", s=10000)
  plt.xlim(lim_inf,lim_sup)
  plt.xlabel(u"$Longitud\ de\ onda\ [\AA]$")
  plt.title(u"$Líneas\ de\ FE\ I$")
  plt.show()
  
  #%%
  
  encuentra = long_nave[(long_nave < lim_sup) & (long_nave > lim_inf)]
  
  encuentra
  
  #%%
  
  mibisec = np.loadtxt("./lineas/bisec_4592.txt")
  
  plt.figure(figsize=(15,15))
  plt.scatter(mibisec[0,0],mibisec[0,1])
  plt.scatter(mibisec[2:,0],mibisec[2:,1])
  plt.ticklabel_format(useOffset=False)
  plt.show()
  