I have a dataframe with this data and want to plot it with a bar graph with x-axis labels being months

import pandas as pd

data = {'Birthday': ['1900-01-31', '1900-02-28', '1900-03-31', '1900-04-30', '1900-05-31', '1900-06-30', '1900-07-31', '1900-08-31', '1900-09-30', '1900-10-31', '1900-11-30', '1900-12-31'],
        'Players': [32, 25, 27, 19, 27, 18, 18, 21, 23, 21, 26, 23]}
df = pd.DataFrame(data)

  Birthday Players
1900-01-31      32
1900-02-28      25
1900-03-31      27
1900-04-30      19
1900-05-31      27
1900-06-30      18
1900-07-31      18
1900-08-31      21
1900-09-30      23
1900-10-31      21
1900-11-30      26
1900-12-31      23

This is what I have

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

fig = plt.figure(figsize=(12, 7))
locator = mdates.MonthLocator()
fmt = mdates.DateFormatter('%b')
X = plt.gca().xaxis
X.set_major_locator(locator)
X.set_major_formatter(fmt)
plt.bar(month_df.index, month_df.Players, color = 'maroon', width=10)

but the result is this with the label starting from Feb instead of Jan

CodePudding user response：

I'm not familiar with matplotlib.dates but because you are using pandas there are simple ways doing what you need using pandas.

Here is my code:

import pandas as pd
import calendar
from matplotlib import pyplot as plt

# read data
month_df = pd.read_csv('data.csv', delim_whitespace=True)

# convert column to datetime
month_df["Birthday"] = pd.to_datetime(month_df["Birthday"], format="%Y-%m-%d")

# group by month and plot a bar plot
month_df.groupby(month_df["Birthday"].dt.month).sum().plot(kind="bar", color = "maroon")

# set plot properties
plt.ylabel("Count")
plt.xlabel("Birthday Month")
plt.xticks(ticks = range(0,12) ,labels = calendar.month_name[1:])

# show plot
plt.show()

Output:

CodePudding user response：

Typically, matplotlib.bar does not do a very good job with datetimes for various reasons. It's easy to manually set your x tick locations and labels as below. This a

CodePudding user response：

• Bar plot x-axis tick locations are 0 indexed, not datetimes
• This solution applies to any plot with a discrete axis (e.g. bar, hist, heat, etc).
• Similar to this
  • If there are many repeated months, where the data must be aggregated, then combine the data using pandas.DataFrame.groupby and aggregate some function like .mean() or .sum()

  dfg = df.groupby('month').Players.sum()
  
  ax = dfg.plot(kind='bar', figsize=(12, 7), rot=0, legend=False)