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 arelist
type. - 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 fromstr
tolist
if 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.plot
xticks=df.index
will 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.explode
to 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')