CODEWITHSUNDEEP
pythonmatplotlibbar-chartdata-visualizationseaborn
Pratyush Saxena
Pratyush Saxena

Reputation: 75

Different bar plot for same x-axis value

I'm having a data-frame as follows:

match_id    team    team_score
  411       RCB       263
 7937       KKR       250
  620       RCB       248
  206       CSK       246
11338       KKR       241
   61       CSK       240
  562       RCB       235

Now, I want to plot a bar plot for all these values as an individual bars, what I'm getting in output is something different:

Bar Plot Output

Is there any way I can make different bars for same x-axis values??

Upvotes: 0

Views: 860

Answers (1)

JohanC
JohanC

Reputation: 80439

When 'team' is used as x, all the values for each team are averaged and a small error bar shows a confidence interval. To have each entry of the table as a separate bar, the index of the dataframe can be used for x. After creating the bars, they can be labeled with the team names.

Optionally, hue='team'colors the bars per team. Then dodge=False is needed to have the bars positioned nicely. In that case, Seaborn also creates a legend, which is not so useful, as the same information now also is present as the x-values. The legend can be suppressed via ax.legend_.remove().

from matplotlib import pyplot as plt
import pandas as pd
from io import StringIO
import seaborn as sns

data_str = StringIO("""match_id    team    team_score
  411       RCB       263
 7937       KKR       250
  620       RCB       248
  206       CSK       246
11338       KKR       241
   61       CSK       240
  562       RCB       235""")
df = pd.read_csv(data_str, delim_whitespace=True)
color_dict = {'RCB': 'dodgerblue', 'KKR': 'darkviolet', 'CSK': 'gold'}
ax = sns.barplot(x=df.index, y='team_score', hue='team', palette=color_dict, dodge=False, data=df)
ax.set_xticklabels(df['team'])
ax.legend_.remove()
plt.tight_layout()
plt.show()

resulting plot

Upvotes: 1

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