Seaborn pairplot not running only on a specific system

Question

I have the following data with the name 'Salaries.csv'. It looks like the following:[The dataset has some columns like Index(['yearID', 'teamID', 'lgID', 'salary', 'num_feat'], dtype='object'). Please note that the column num_feat I have added to the DataFrame.

I want to do a Seaborn pairplot for team 'ATL' to plot scatter plots among all numeric features in the data frame.

I have the following code :

import seaborn as sns

var_set = [
    "yearID",
    "teamID",
    "lgID",
    "playerID",
    "salary"
]

head_set = []
head_set.extend(var_set)
head_set.append("num_feat")

df = pd.read_csv('Salaries.csv',index_col='playerID', header=None, names=head_set)

df['num_feat'] = 100 * np.random.random_sample(df.shape[0]). #Adding column num_feat

df_copy = df
cols_with_team_ATL = df_copy.loc[df_copy.teamID=="ATL", ]

# Create the default pairplot
pairplot_fig = sns.pairplot(cols_with_team_ATL, vars=['yearID', 'salary', 'num_feat'])
plt.subplots_adjust(top=0.9)
pairplot_fig.fig.suptitle("Scatter plots among all numeric features in the data frame for teamID = ATL", fontsize=18, alpha=0.9, weight='bold')
plt.show()

The same code runs perfectly on my friend's system but not on mine. It shows the following error in my system :

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/ch/6r9p7n0j3xg1l79lz1zdkvsh0000gq/T/ipykernel_97373/3735184261.py in <module>
     25 # Create the default pairplot
     26 print(df.columns)
---> 27 pairplot_fig = sns.pairplot(cols_with_team_ATL, vars=['yearID', 'salary', 'num_feat'])
     28 plt.subplots_adjust(top=0.9)
     29 pairplot_fig.fig.suptitle("Scatter plots among all numeric features in the data frame for teamID = ATL", fontsize=18, alpha=0.9, weight='bold')

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/_decorators.py in inner_f(*args, **kwargs)
     44             )
     45         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 46         return f(**kwargs)
     47     return inner_f
     48 

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/axisgrid.py in pairplot(data, hue, hue_order, palette, vars, x_vars, y_vars, kind, diag_kind, markers, height, aspect, corner, dropna, plot_kws, diag_kws, grid_kws, size)
   2124     diag_kws.setdefault("legend", False)
   2125     if diag_kind == "hist":
-> 2126         grid.map_diag(histplot, **diag_kws)
   2127     elif diag_kind == "kde":
   2128         diag_kws.setdefault("fill", True)

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/axisgrid.py in map_diag(self, func, **kwargs)
   1476             plot_kwargs.setdefault("hue_order", self._hue_order)
   1477             plot_kwargs.setdefault("palette", self._orig_palette)
-> 1478             func(x=vector, **plot_kwargs)
   1479             ax.legend_ = None
   1480 

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/distributions.py in histplot(data, x, y, hue, weights, stat, bins, binwidth, binrange, discrete, cumulative, common_bins, common_norm, multiple, element, fill, shrink, kde, kde_kws, line_kws, thresh, pthresh, pmax, cbar, cbar_ax, cbar_kws, palette, hue_order, hue_norm, color, log_scale, legend, ax, **kwargs)
   1460     if p.univariate:
   1461 
-> 1462         p.plot_univariate_histogram(
   1463             multiple=multiple,
   1464             element=element,

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/distributions.py in plot_univariate_histogram(self, multiple, element, fill, common_norm, common_bins, shrink, kde, kde_kws, color, legend, line_kws, estimate_kws, **plot_kws)
    426 
    427         # First pass through the data to compute the histograms
--> 428         for sub_vars, sub_data in self.iter_data("hue", from_comp_data=True):
    429 
    430             # Prepare the relevant data

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/_core.py in iter_data(self, grouping_vars, reverse, from_comp_data)
    981 
    982         if from_comp_data:
--> 983             data = self.comp_data
    984         else:
    985             data = self.plot_data

~/USC/anaconda3/lib/python3.9/site-packages/seaborn/_core.py in comp_data(self)
   1055                     orig = self.plot_data[var].dropna()
   1056                 comp_col = pd.Series(index=orig.index, dtype=float, name=var)
-> 1057                 comp_col.loc[orig.index] = pd.to_numeric(axis.convert_units(orig))
   1058 
   1059                 if axis.get_scale() == "log":

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/indexing.py in __setitem__(self, key, value)
    721 
    722         iloc = self if self.name == "iloc" else self.obj.iloc
--> 723         iloc._setitem_with_indexer(indexer, value, self.name)
    724 
    725     def _validate_key(self, key, axis: int):

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/indexing.py in _setitem_with_indexer(self, indexer, value, name)
   1730             self._setitem_with_indexer_split_path(indexer, value, name)
   1731         else:
-> 1732             self._setitem_single_block(indexer, value, name)
   1733 
   1734     def _setitem_with_indexer_split_path(self, indexer, value, name: str):

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/indexing.py in _setitem_single_block(self, indexer, value, name)
   1966 
   1967         # actually do the set
-> 1968         self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
   1969         self.obj._maybe_update_cacher(clear=True)
   1970 

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/internals/managers.py in setitem(self, indexer, value)
    353 
    354     def setitem(self: T, indexer, value) -> T:
--> 355         return self.apply("setitem", indexer=indexer, value=value)
    356 
    357     def putmask(self, mask, new, align: bool = True):

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/internals/managers.py in apply(self, f, align_keys, ignore_failures, **kwargs)
    325                     applied = b.apply(f, **kwargs)
    326                 else:
--> 327                     applied = getattr(b, f)(**kwargs)
    328             except (TypeError, NotImplementedError):
    329                 if not ignore_failures:

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/internals/blocks.py in setitem(self, indexer, value)
    941 
    942         # length checking
--> 943         check_setitem_lengths(indexer, value, values)
    944         exact_match = is_exact_shape_match(values, arr_value)
    945 

~/USC/anaconda3/lib/python3.9/site-packages/pandas/core/indexers.py in check_setitem_lengths(indexer, value, values)
    174                     and len(indexer[indexer]) == len(value)
    175                 ):
--> 176                     raise ValueError(
    177                         "cannot set using a list-like indexer "
    178                         "with a different length than the value"

ValueError: cannot set using a list-like indexer with a different length than the value

Why is it not running particularly on my system? Is there any problem with the python version or Jupyter Notebook?

Please help.