Which factors are highly correlated with not repaying loans?

In [4]:
col = high_corr_for_graphs[0]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()

/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:829: RuntimeWarning: invalid value encountered in greater_equal
  keep = (tmp_a >= first_edge)
/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:830: RuntimeWarning: invalid value encountered in less_equal
  keep &= (tmp_a <= last_edge)
In [5]:
col = high_corr_for_graphs[1]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()
In [6]:
col = high_corr_for_graphs[2]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()

/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:829: RuntimeWarning: invalid value encountered in greater_equal
  keep = (tmp_a >= first_edge)
/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:830: RuntimeWarning: invalid value encountered in less_equal
  keep &= (tmp_a <= last_edge)
In [7]:
col = high_corr_for_graphs[3]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()

/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:829: RuntimeWarning: invalid value encountered in greater_equal
  keep = (tmp_a >= first_edge)
/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:830: RuntimeWarning: invalid value encountered in less_equal
  keep &= (tmp_a <= last_edge)
In [8]:
col = high_corr_for_graphs[4]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()
In [9]:
col = high_corr_for_graphs[5]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()
In [10]:
col = high_corr_for_graphs[6]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()

/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:829: RuntimeWarning: invalid value encountered in greater_equal
  keep = (tmp_a >= first_edge)
/Users/danielcaraway/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:830: RuntimeWarning: invalid value encountered in less_equal
  keep &= (tmp_a <= last_edge)
In [11]:
col = high_corr_for_graphs[7]
df = app_train.copy()
df[col] = abs(df[col])
plt.style.use('fivethirtyeight')
plt.hist(df[col] / 365, edgecolor = 'k', bins = 25)
plt.title(col); plt.xlabel('x'); plt.ylabel('Count');
plt.show()

Fin.

In [ ]: