Pandas notes

From DiLab

Jump to: navigation, search


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)}

df = pd.DataFrame( rows )

Remove a column

columns = ['Col1', 'Col2', ...]
df.drop(columns, inplace=True, axis=1)

Plot options

Many visualization examples are here.

Define the colors of the plot data


Different plot types (markers)


Limit the X axis values:


Naming the axis

ax = df.plot()

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()

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);
Personal tools