I have a Dataframe with the column 'all_maxs' that could have a list of different values.
c all_maxs 38 50804.6 [50883.3] 39 50743.9 [50883.3] 40 50649.9 [50883.3] 41 50508.3 [50883.3] 42 50577.6 [50883.3] 43 50703.0 [50883.3] 44 50793.7 [50883.3] 45 50647.8 [50883.3, 50813.1] 46 50732.8 [50883.3, 50813.1] 47 50673.2 [50883.3, 50813.1] df.plot(y='c')
Current Result
I need to plot column 'c', and the values of column 'all_maxs' that should be horizontal lines.
Expected Result

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Answer
- Verify the
'all_maxs'values arelisttype. - Extract values from the lists and plot them as horizontal lines.
df = df.dropna()if there are anyNaN
Imports and DataFrame
- Convert the
'all_maxs'column type fromstrtolistif needed, usingast.liter_eval
import pandas as pd
from ast import literal_eval
data =
{38: {'all_maxs': '[50883.3]', 'c': 50804.6},
39: {'all_maxs': '[50883.3]', 'c': 50743.9},
40: {'all_maxs': '[50883.3]', 'c': 50649.9},
41: {'all_maxs': '[50883.3]', 'c': 50508.3},
42: {'all_maxs': '[50883.3]', 'c': 50577.6},
43: {'all_maxs': '[50883.3]', 'c': 50703.0},
44: {'all_maxs': '[50883.3]', 'c': 50793.7},
45: {'all_maxs': '[50883.3, 50813.1]', 'c': 50647.8},
46: {'all_maxs': '[50883.3, 50813.1]', 'c': 50732.8},
47: {'all_maxs': '[50883.3, 50813.1]', 'c': 50673.2}}
df = pd.DataFrame.from_dict(data, orient='index')
# reorder the columns to match the OP
df = df[['c', 'all_maxs']]
# print a value from all_maxs to see the type
>>> print(type(df.loc[38, 'all_maxs']))
str
# currently the all_max values are strings, which must be converted to list type
df.all_maxs = df.all_maxs.apply(literal_eval)
# print a value from all_maxs to see the type
>>> print(type(df.loc[38, 'all_maxs']))
list
Plot
- Plot the dataframe directly with
pandas.DataFrame.plotxticks=df.indexwill make an xtick for every value in the index, but if there are many values crowding the x-axis, remove this parameter.
- Use
matplotlib.pyplot.hlines, which will accept a list of values, to plot the unique values from'all_max'as horizontal lines.- Use
pandas.DataFrame.explodeto remove all the values from lists, and then drop duplicates with.drop_duplicates y=will be the remaining values in the'all_maxs'columnxmin=will be the remaining index valuesxmax=will be the max value in the index plotted fromdf
- Use
ax = df.plot(y='c', legend=False, figsize=(8, 5), xticks=df.index) # extract all the values from all_maxs, drop the duplicates all_maxs = df.all_maxs.explode().drop_duplicates().to_frame() # add the horizontal lines ax.hlines(y=all_maxs.all_maxs, xmin=all_maxs.index, xmax=df.index.max(), color='k')

