Plotting more than one histogram in a shape with matplotlib

Question

I need to write code for a function in a helper class that would draw a few histograms in the figure. With the code below, I get a ValueError: too many values ​​to unpack. on the command line: there are more variables than values, or vice versa. What am I doing wrong?

def draw_histograms(df, variables, n_rows, n_cols):
    fig = plt.figure()
    for n_rows, n_cols, plot_number in df:
        fig.add_subplot(n_rows, n_cols, plot_number)
    plt.show()

        """ variables includes a list of variables you need to draw histograms for. 
n_rows and n_cols specifies the number of subplots you need to have in a figure. 
If n_rows =3 and n_cols =2, there will 3*2 = 6 subplots placed in a grid of 3 rows and 2 columns.
subplot(321) is identical to subplot(3,2,1), which refers to the 1st subplot in a grid of 3 rows and 2 columns"""

util.draw_histograms(df, variables = ['DerogCnt', 'CollectCnt', 'InqCnt06', 'InqTimeLast', 'InqFinanceCnt24', 'TLTimeFirst', 'TLTimeLast', 'TLCnt03', 'TLCnt12'], 3,3) 

This is what df looks like. Variables do not include all of them, since irrelevant ones were deleted.

TARGET   ID  DerogCnt  CollectCnt  BanruptcyInd  InqCnt06  InqTimeLast  \
0       0   66         1           1             0         7            1   
1       0  116         1           1             0         2            1   
2       0  124         0           0             0         1            1   
3       0  128         0           0             0         6            3   
4       0  143         0           0             0         1            0   
   InqFinanceCnt24  TLTimeFirst  TLTimeLast     ...       TL50UtilCnt  \
0                4          125           3     ...                 4   
1                0          252          18     ...                 2   
2                4          254          12     ...                 3   
3                6          154           3     ...                 5   
4                1          311          17     ...                 3   

   TLBalHCPct  TLSatPct  TLDel3060Cnt24  TLDel90Cnt24  TLDel60CntAll  \
0        0.85      0.67               0             0              1   
1        0.48      0.30               0             1              4   
2        0.84      0.67               0             1              1   
3        0.73      0.76               0             1              1   
4        0.88      0.63               0             0              1   

   TLOpenPct  TLBadDerogCnt  TLDel60Cnt24  TLOpen24Pct  
0       0.58              0             0         0.71  
1       0.40              2             1         0.50  
2       0.50              1             1         0.33  
3       0.53              1             1         1.22  
4       0.63              0             0         0.20  

Here

Answer 1

, , "", , (. ). , for, df.hist() layout, (n_row, n_col).

df = pd.DataFrame(data=np.random.random(size=(50, 6)), columns=[i for i in string.ascii_lowercase[:6]])
df.hist(layout=(3,2))
plt.show()

df for:

for n_rows, n_cols, plot_number in df:

df , column.

. :

df = pd.DataFrame(data=np.random.random(size=(5, 5)), columns=[i for i in string.ascii_lowercase[:5]])

print([i for i in df])

['a', 'b', 'c', 'd', 'e']

ValueError , n_rows, n_cols, plot_number , . for ... in df.items(), , : :

for i, col in df.items():
    print('\n', i)
    print(col)

 a
0    0.640400
1    0.683003
2    0.807806
3    0.767698
4    0.648523
Name: a, dtype: float64

 b
0    0.774166
1    0.052386
2    0.235688
3    0.018334
4    0.492798
Name: b, dtype: float64

 c
0    0.390146
1    0.383680
2    0.588734
3    0.911859
4    0.901137
Name: c, dtype: float64

 d
0    0.455289
1    0.626278
2    0.977627
3    0.311236
4    0.570580
Name: d, dtype: float64

 e
0    0.782046
1    0.041161
2    0.226500
3    0.331402
4    0.942302
Name: e, dtype: float64