pandas error when reading file - pandas

Question

I am new to jupyter and have been trying to plot using it only last week. I have huge excel sheets .csv format that I want to read and plot. I am doing it by converting the .csv to a .dat format.
My code looks like this
import numpy as np
import pandas as pd
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
file1 = 'king2.dat'
file2 = 'iso.dat'
data1 = pd.read_csv(file1, delimiter='\s+', header=None, engine='python')
data1.columns = ['no_plt', 'Op_RA_plt', 'Op_DE_plt', 'Vmag_plt', 'B-
V_plt', '(B-V)o_plt', 'no_2_plt', 'FUV_mag_plt','FUV_magerr_plt',
'(FUV-V)_plt', '(V-I)_plt', '(FUV-I)_plt',
'no_op_2M','Op_RA_2M','Op_DE_2M','Vmag_2M','(B-V)o_2M',
'FUV_mag_2M','FUV-V_2M','no_2M','j_m_2M','h_m_2M','k_m_2M','j-h_2M',
'h-k_2M','j-k_2M','(V-I)_2M','(FUV-I)_2M',
'no_MS','Op_RA_MS','Op_DE_MS','Vmag_MS','(B-V)o_MS',
'FUV_mag_MS','FUV-V_MS','(V-I)_MS','(FUV-I)_MS',
'no_508','Op_RA_508','Op_DE_508','Vmag_508','(B-V)o_508',
'FUV_mag_508','FUV-V_508', '(V-I)_508','(FUV-I)_508',
'no_RG','Op_RA_RG','Op_DE_RG','Vmag_RG','(B-V)o_RG','FUV_mag_RG',
'FUV-V_RG','(V-I)_RG','(FUV-I)_RG','no_RG609','Op_RA_RG609',
'Op_DE_RG609','Vmag_RG609','(B-V)o_RG609','FUV_mag_RG609',
'FUV-V_RG609', '(V-I)_RG609', '(FUV-I)_RG609',
'no_TF621','Op_RA_TF621','Op_DE_TF621','Vmag_TF621','(B-V)o_TF621',
'FUV_mag_TF621','FUV-V_TF621','(V-I)_TF621','(FUV-I)_TF621',
'no_onBSS','Op_RA_onBSS','Op_DE_onBSS','Vmag_onBSS','(B-V)o_onBSS',
'FUV_mag_onBSS','FUV-V_onBSS','(V-I)_onBSs','(FUV-I)_onBSS',
'no_BSSreg','Op_RA_BSSreg','Op_DE_BSSreg','Vmag_BSSreg',
'(B-V)o_BSSreg','FUV_mag_BSSreg','FUV-V_BSSreg','(V-I)_BSSreg',
'(FUV-I)_BSSreg','no_BSSreg558', 'Op_RA_BSSreg558' , 'Op_DE_BSSreg558','Vmag_BSSreg558','(B-V)o_BSSreg558',
'FUV_mag_BSSreg558','FUV-V_BSSreg558','(V-I)_BSSreg558','(FUV-I)_BSSreg558','no_aMS','Op_RA_aMS',
'Op_DE_aMS','Vmag_aMS','(B-V)o_aMS','FUV_mag_aMS','FUV-V_aMS','(V-I)_aMS','(FUV-I)_aMS','no_bMS',
'Op_RA_bMS','Op_DE_bMS','Vmag_bMS','(B-V)o_bMS','FUV_mag_bMS','FUV-V_bMS','(V-I)_bMS',
'(FUV-I)_bMS','no _SED','Op_RA _SED','Op_DE _SED','Vmag _SED','(B-V)o _SED','FUV_mag _SED',
'FUV-V _SED','(V-I)_SED','(FUV-I)_SED']
data2 = pd.read_csv(file1, delimiter='\s+', header=None, engine='python')
data2.columns =['age','log(Z)','mass','logl','logt','logg',
'FUVCa_14.76','NUVB15_14.76', '(FUV-NUV)14.76','V14.76','B14.76',
'B-V14.76','(FUV-V)14.76','(NUV-V)14.76','GA NUV14.76',
'(Uf-Gn)14.76','I14.76','(V-I)14.76','(FUV-I)14.76']
def fit_data():
fig = plt.figure(1,figsize=(8,8))
plt.subplot(111)
plt.scatter(data1['(B-V)o_plt'], data1['Vmag_plt'], marker='.', color='r', s=5)
plt.scatter(data2['B-V14.76'], data2['V14.76'], marker='o', color='g', s=6)
plt.xlabel('RA_F',size=20)
plt.ylabel('DEC_F',size=20)
plt.gca().invert_xaxis()
plt.gca().invert_yaxis()
plt.show()
plt.close()
fit_data()
When I had sheets of 4 columns, it would read and plot without any errors. But if I increase the columns, it gives me the error:
ParserError Traceback (most recent call last)
<ipython-input-5-fe66f2a2aac9> in <module>()
13 data1.columns = ['age','FUVCa','NUVB15','(FUV-NUV)','V','B','B-V','(FUV-V)','(NUV-V)','I','(V-I)','(FUV-I)']
14
---> 15 data2 = pd.read_csv(file2, delimiter='\s+', header=None, engine='python')
16 data2.columns = ['no','Op_RA','Op_DE','Vmag','(B-V)o','FUV_mag','(FUV-V)','(V-I)','(FUV-I)', 'no_MS','Op_RA_MS','Op_DE_MS','Vmag_MS','(B-V)o_MS',
17 'FUV_mag_MS','FUV-V_MS','(V-I)_MS','(FUV-I)_MS','no_508','Op_RA_508','Op_DE_508','Vmag_508',
~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)
707 skip_blank_lines=skip_blank_lines)
708
--> 709 return _read(filepath_or_buffer, kwds)
710
711 parser_f.__name__ = name
~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds)
453
454 try:
--> 455 data = parser.read(nrows)
456 finally:
457 parser.close()
~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py in read(self, nrows)
1067 raise ValueError('skipfooter not supported for iteration')
1068
-> 1069 ret = self._engine.read(nrows)
1070
1071 if self.options.get('as_recarray'):
~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py in read(self, rows)
2261 content = content[1:]
2262
-> 2263 alldata = self._rows_to_cols(content)
2264 data = self._exclude_implicit_index(alldata)
2265
~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py in _rows_to_cols(self, content)
2916 msg += '. ' + reason
2917
-> 2918 self._alert_malformed(msg, row_num + 1)
2919
2920 # see gh-13320
~/anaconda3/lib/python3.6/site-packages/pandas/io/parsers.py in _alert_malformed(self, msg, row_num)
2683
2684 if self.error_bad_lines:
-> 2685 raise ParserError(msg)
2686 elif self.warn_bad_lines:
2687 base = 'Skipping line {row_num}: '.format(row_num=row_num)
ParserError: Expected 30 fields in line 21, saw 45. Error could possibly be due to quotes being ignored when a multi-char delimiter is used.
I wasn't able to understand what it means. I don't know where I am going wrong or if I am giving too many columns for it to handle.
Line 20
508 12.76968 58.18559 18.97 0.96 0.65 1371 22.925 0.343 3.955 508 12.76968 58.18559 18.97 0.65 22.925 3.955 32 16.111 15.777 15.253 0.334 0.524 0.858 508 12.76968 58.18559 18.97 0.65 22.925 3.955 508 12.76968 58.18559 18.97 0.65 22.925 3.955
Line 21
508 12.76968 58.18559 18.97 0.96 0.65 1371 22.925 0.343 3.955 508 12.76968 58.18559 18.97 0.6522.925 3.955 32 16.111 15.777 15.253 0.334 0.524 0.858 508 12.76968 58.18559 18.97 0.65 22.925 3.955 508 12.76968 58.18559 18.97 0.65 22.925 3.955 508 12.76968 58.18559 18.97 0.65 22.925 3.955