CODEWITHSUNDEEP
pythonfor-loopmatplotlibdata-visualization
Jasper_97
Jasper_97

Reputation: 27

Plotting multiple graphs on one figure generated from for loop

I have a dictionary of data frames and I am using the below code to generate a stacked bar chart for every data frame within the dict. The code prints every stacked bar chart as intended (each graph one after the other and below each other in notebook), but I want it to print each chart on one figure, lets say 4 rows with 3 columns for example.

for i, key in enumerate(d):
    plt.rcParams["figure.figsize"] = (5,3)
    d[key].plot(kind = 'barh', width= 0.85, stacked = True, color = ['limegreen','gold', 'orange', 'red'])
    plt.legend(bbox_to_anchor = (1.05, 1.025), title = "Categories")
    plt.xlabel('Cumulative Percent')
    plt.gca().xaxis.set_major_formatter(mtick.PercentFormatter())
    plt.ylabel('Data Stream')
    plt.gca().invert_yaxis()
    plt.title(f'{key}')    
plt.show()

Upvotes: 1

Views: 1032

Answers (1)

mujjiga
mujjiga

Reputation: 16916

using subplots:

# sample data
df = pd.DataFrame(
    {f"col_{i}": np.random.randint(0,100, 50) for i in range(12)}
)


fig, axs = plt.subplots(4, 3, figsize=(25,20))
all_axs = axs.ravel()
for i, c in enumerate(df.columns):    
  ax = df[c].plot(kind = 'barh', 
                  width= 0.85, 
                  stacked = True, 
                  color = ['limegreen','gold', 'orange', 'red'], 
                  ax=all_axs[i])
  ax.legend(title = "Categories")
  ax.set_xlabel("Cumulative Percent")
  ax.set_ylabel("Data Stream")
  ax.xaxis.set_major_formatter(mtick.PercentFormatter())
  ax.invert_yaxis()

fig.tight_layout()

output: enter image description here

Upvotes: 1

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