import
numpy as np
import
pandas as pd
import
matplotlib.pyplot as plt
import
seaborn as sns
import
statsmodels.api as sm
%
matplotlib inline
sns.mpl.rcParams[
'figure.figsize'
]
=
(
20.0
,
15.0
)
beam_data
=
pd.read_csv(
'beam_Deflection.txt'
, header
=
None
)
sns.set_style(
'darkgrid'
)
fig, ax
=
plt.subplots(
2
,
2
)
sns.lineplot(x
=
pd.Series(beam_data.index),y
=
beam_data[
0
],ax
=
ax[
0
,
0
])
ax[
0
,
0
].set_title(
'Run Sequence Plot'
)
pd.plotting.lag_plot(beam_data[
0
],ax
=
ax[
0
,
1
])
ax[
0
,
1
].set_title(
'Lag Plot with k=1'
)
sns.histplot(beam_data[
0
],kde
=
True
,ax
=
ax[
1
,
0
])
ax[
1
,
0
].set_title(
'Histogram'
)
sm.ProbPlot(beam_data[
0
]).qqplot(line
=
's'
, ax
=
ax[
1
,
1
],color
=
'blue'
);
ax[
1
,
1
].set_title(
'Normal Probability Plot'
)
fig.suptitle(
'4-plot'
)
plt.show()