CODEWITHSUNDEEP
pythonpandasmatplotlibsubplot
Zebra125
Zebra125

Reputation: 526

How to subplot a dictionary of dataframes

I would like to subplot 16 dataframes from a dictionary, but I tried with for loop but I don't how to finish my code with my DictDataFrame:

DataFrameDict.keys() :
dict_keys([1, 10, 20, 30, 40, 47, 100, 15, 25, 35, 45, 50, 5, 105, 55, 0])

DataFrameDict[0]:

date_time   id  value   Duration_datetime   Duration(Min)

So I would like to subplot each column Duration(Min) for each dataframe from dictionary but I don't know how to deals with : DataFrameDict[key]['Duration(Min)']

fig = plt.figure()
fig, ax = plt.subplots(nrows=4, ncols=4)

for i in range(4):
    for j in range(4):
        subplot = ax[i, j]


plt.show()

Upvotes: 1

Views: 400

Answers (2)

Trenton McKinney
Trenton McKinney

Reputation: 62393

  • Using .ravel to flatten the axes array is fairly common.
  • math.ceil will ensure there are enough rows, when the number of items to plot is not evenly divisible by the number of columns.
  • This for-loop iterates through the enumerated dict keys, using idx to index the correct value from ax_array, and using the key to plot each dataframe.
  • pandas.DataFrame.plot is used to plot the dataframe.
import pandas as pd
import numpy as np  # for test data
import math

# test data
rows = 10
keys = sorted([1, 10, 20, 30, 40, 47, 100, 15, 25, 35, 45, 50, 5, 105, 55, 0])
df_dict = {key: pd.DataFrame({'a': np.random.randint(0, 10, size=(rows)), 'b': np.random.randint(15, 25, size=(rows)), 'Duration(Min)': np.random.randint(30, 40, size=(rows))}) for key in keys}

# determine number of rows, given the number of columns
cols = 4
rows = math.ceil(len(keys) / cols)

# create the figure with multiple axes
fig, axes = plt.subplots(nrows=rows, ncols=cols, figsize=(16, 16))

# convert the axes from a 4x4 array to a 16x1 array
ax_array = axes.ravel()

# iterate through the dataframe dictionary keys and use enumerate
for idx, key in enumerate(keys):
    df_dict[key]['Duration(Min)'].plot(ax=ax_array[idx], ylabel='Value', title=f'DataFrame: {key}')
plt.tight_layout()
plt.show()

enter image description here

Upvotes: 1

Quang Hoang
Quang Hoang

Reputation: 150735

Try flatten the axes array and loop with zip:

fig = plt.figure()
fig, axes = plt.subplots(nrows=4, ncols=4)

for (key, data), ax in zip(DataFrameDict.items(), axes.ravel()):
    data['Duration (Min)'].plot(ax=ax)

    ax.set_title(f'Data for {key}')

plt.show()

Upvotes: 2

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