Difference between revisions of "Pandas notes"
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== Plot options == |
== Plot options == |
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Many https://pandas.pydata.org/pandas-docs/stable/visualization.html visualization examples are here]. |
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Define the colors of the plot data |
Define the colors of the plot data |
Revision as of 14:40, 26 October 2017
Using Python Pandas package for data analysis. Leo's notes.
Importing and setup
Some useful imports for the examples below:
import pandas as pd import numpy as np import matplotlib.pyplot as plt import matplotlib matplotlib.rc('figure', figsize=(15, 5))
Data manipulation
Import data from a CSV file to a dataframe
df = pd.read_csv("filename.csv")
Filter the data by a field value
df2 = df.loc[df['Tagid'] == "1234"]
Get all unique values (for example, for the Tagid field)
allTags = df.Tagid.unique()
Pivot the table, where the values become columns. For example, to create a plot that uses unique values (of Tagid) as the series.
dfTags = df.pivot(columns='Tagid', values='RSSI')
Creating a data frame on the run:
rows = [] for x in mylist : rec = {"Name" : x, "AA" : aa(x), "BB" : bb(x)} rows.append(rec) df = pd.DataFrame( rows )
Plot options
Many https://pandas.pydata.org/pandas-docs/stable/visualization.html visualization examples are here].
Define the colors of the plot data
df.plot(color="rgbk")
Different plot types (markers)
df.plot(marker='.')
Limit the X axis values:
df.plot(xlim=(0,4000))
Naming the axis
ax = df.plot() ax.set_ylabel(AntNames[x])
Placement of the legend (Below-left of the plot)
df.plot().legend(loc='upper left', bbox_to_anchor=(0, 0))
Removing the legend
ax = df.plot() ax.legend_.remove()
Plotting means and std: link
mymean = byTagAnt.RSSI.mean() mystd = byTagAnt.RSSI.std() mymean.plot(kind="bar", yerr=mystd);
Plotting with various parameters:
p = mymean.plot(figsize=(15,5), legend=False, kind="bar", rot=45, color="green", fontsize=16, yerr=mystd); p.set_title("RSSI", fontsize=18); p.set_xlabel("Tags", fontsize=18); p.set_ylabel("dBm", fontsize=18); p.set_ylim(0,-85);