Summary

Specialisation	Data Analysis and Interpretation
Course	Data Management and Visualisation
Education Institution	Wesleyan University
Publisher	Coursera
Assignment	Running Your Second Program

Exploratory Data Analysis

Source

The Mars Craters data set was made available by Wesleyan University/Coursera as part of the Data Management and Visualisation course, of the Data Analysis and Interpretation Specialisation, from the Ph.D. Thesis Planetary Surface Properties, Cratering Physics, and the Volcanic History of Mars from a New Global Martian Crater Database (2011) by Robbins, S.J., University of Colorado at Boulder.

Size

The data set has a total of 384343 observations and 10 variables.

The variables are: CRATER_ID, CRATER_NAME, LATITUDE_CIRCLE_IMAGE, LONGITUDE_CIRCLE_IMAGE, DIAM_CIRCLE_IMAGE, DEPTH_RIMFLOOR_TOPOG, MORPHOLOGY_EJECTA_1, MORPHOLOGY_EJECTA_2, MORPHOLOGY_EJECTA_3 and NUMBER_LAYERS.

Univariate Analysis

Hemisphere

Hemisphere is a variable derived from the LATITUDE_CIRCLE_IMAGE variable to transform the continuous coordinates into categories, for the sake of brevity.

Hemisphere shows seven occurrences in the Equator, same as Latitude equals to zero. Just above 60% of the observations are located in the South Hemisphere. Also, all the observations have values.

Quadrangle

Quadrangle is a variable derived from both LATITUDE_CIRCLE_IMAGE and LONGITUDE_CIRCLE_IMAGE variables. (see below a definition from Wikipedia)

Each Quadrangle has approximatelly from one to five percent of the recorded craters, being MC-16, Memnonia the one with the most observations (20455 = 5.32%), and MC-10: Lunae Palus the one with the lower number of records (3478 = 0.90%).

List of quadrangles on Mars (Wikipedia):

The surface of Mars has been divided into 30 quadrangles by the United States Geological Survey, so named because their borders lie along lines of latitude and longitude and so maps appear rectangular. Martian quadrangles are named after local features and are numbered with the prefix “MC” for “Mars Chart”. West longitude is used.

The following imagemap of the planet Mars is divided into 30 linked quadrangles. Click on the quadrangle and you will be taken to the corresponding article pages. North is at the top; 0°N 180°W is at the far left on the equator. The map images were taken by the Mars Global Surveyor.

From Wikipedia, Source: http://photojournal.jpl.nasa.gov/catalog/PIA03467

Ejecta Morphology 1 (Group by Main Feature)

The variable MORPHOLOGY_EJECTA_1 has 339718 out of 384343 values missing, or 88.3%. The recording with existing content are divided in a large number of categories if considered the full morphology qualification. If taken into account just the first classification, the number of categories is reduced to 29.

From the recorded data, considering just the first classification, shows that 27069, or 60.6%, are of the RD category. The only two other categories that have more than 10% are SLERS (11.45% = 5111) and SLEPS (11.20% = 4998).

Ejecta Morphology 2 (Group by Main Feature)

The variable MORPHOLOGY_EJECTA_2 has 364867 out of 384343 values missing, or 94.9%. The recording with existing content are divided in a large number of categories if considered the full morphology qualification. If taken into account just the first classification, the number of categories is reduced to 10.

From the recorded data, considering just the first classification, shows that 6540, or 33.6%, are of the HUSL category. The only two other categories that have more than 10% are HUBS (4459 = 22.9%) and SMSL (2797 = 14.3%).

Ejecta Morphology 3 (Group by Main Feature)

The variable MORPHOLOGY_EJECTA_3 has 383050 out of 384343 values missing, or 99.6%. The recording with existing content are divided in a large number of categories if considered the full morphology qualification. If taken into account just the first classification, the number of categories is reduced to 24.

From the recorded data, considering just the first classification, shows that 351, or 27.1%, are of the PIN-CUSHION category. The other category that has more than 10% is SMALL-CROWN (20.6% = 267).

Maximum Number of Cohesive Layers

The NUMBER_LAYERS variable has six categories (0, 1, 2, 3, 4 and 5) and none of its observations are missing. The vast majority of craters are identified as having “0” layers, counting 364612, or 94.87% of the records.

Using SAS

Code

/* Use Course's Library */
LIBNAME mydata "/courses/d1406ae5ba27fe300" ACCESS = readonly;

/* Configure the Data */
DATA NEW;
  /* Data set */
  SET   mydata.marscrater_pds;
  LABEL Hemisphere    = "Hemisphere"
        Quadrangles   = "Quadrangles"
        MorphoE1U     = "Ejecta Morphology 1 (Group by Main Feature)"
        MorphoE2U     = "Ejecta Morphology 2 (Group by Main Feature)"
        MorphoE3U     = "Ejecta Morphology 3 (Group by Main Feature)"
        NUMBER_LAYERS = "Maximum Number of Cohesive Layers";

  /* Categorise the Latitude in Hemispheres */
  IF (LATITUDE_CIRCLE_IMAGE < 0)
    THEN Hemisphere = "South  ";
    ELSE IF (LATITUDE_CIRCLE_IMAGE > 0)
      THEN Hemisphere = "North  ";
      ELSE Hemisphere = "Equator";

  /* convert coordinates to Quadrangles: https://en.wikipedia.org/wiki/List_of_quadrangles_on_Mars */
  LA = LATITUDE_CIRCLE_IMAGE;
  LO = LONGITUDE_CIRCLE_IMAGE + 180;
  IF LA >=  65 AND LA <=  90 AND LO >=   0 AND LO <= 360 THEN Quadrangle = "MC-01: Mare Boreum (North Pole)";
  IF LA >=  30 AND LA <   65 AND LO >= 120 AND LO <  180 THEN Quadrangle = "MC-02: Diacria";
  IF LA >=  30 AND LA <   65 AND LO >=  60 AND LO <  120 THEN Quadrangle = "MC-03: Arcadia";
  IF LA >=  30 AND LA <   65 AND LO >=   0 AND LO <   60 THEN Quadrangle = "MC-04: Mare Acidalium";
  IF LA >=  30 AND LA <   65 AND LO >= 300 AND LO <= 360 THEN Quadrangle = "MC-05: Ismenius Lacus";
  IF LA >=  30 AND LA <   65 AND LO >= 240 AND LO <  300 THEN Quadrangle = "MC-06: Casius";
  IF LA >=  30 AND LA <   65 AND LO >= 180 AND LO <  240 THEN Quadrangle = "MC-07: Cebrenia";
  IF LA >=   0 AND LA <   30 AND LO >= 135 AND LO <  180 THEN Quadrangle = "MC-08: Amazonis";
  IF LA >=   0 AND LA <   30 AND LO >=  90 AND LO <  135 THEN Quadrangle = "MC-09: Tharsis";
  IF LA >=   0 AND LA <   30 AND LO >=  45 AND LO <   90 THEN Quadrangle = "MC-10: Lunae Palus";
  IF LA >=   0 AND LA <   30 AND LO >=   0 AND LO <   45 THEN Quadrangle = "MC-11: Oxia Palus";
  IF LA >=   0 AND LA <   30 AND LO >= 315 AND LO <= 360 THEN Quadrangle = "MC-12: Arabia";
  IF LA >=   0 AND LA <   30 AND LO >= 270 AND LO <  315 THEN Quadrangle = "MC-13: Syrtis Major";
  IF LA >=   0 AND LA <   30 AND LO >= 225 AND LO <  270 THEN Quadrangle = "MC-14: Amenthes";
  IF LA >=   0 AND LA <   30 AND LO >= 180 AND LO <  225 THEN Quadrangle = "MC-15: Elysium";
  IF LA >= -30 AND LA <    0 AND LO >= 135 AND LO <  180 THEN Quadrangle = "MC-16: Memnonia";
  IF LA >= -30 AND LA <    0 AND LO >=  90 AND LO <  135 THEN Quadrangle = "MC-17: Phoenicis Lacus";
  IF LA >= -30 AND LA <    0 AND LO >=  45 AND LO <   90 THEN Quadrangle = "MC-18: Coprates";
  IF LA >= -30 AND LA <    0 AND LO >=   0 AND LO <   45 THEN Quadrangle = "MC-19: Margaritifer Sinus";
  IF LA >= -30 AND LA <    0 AND LO >= 315 AND LO <= 360 THEN Quadrangle = "MC-20: Sinus Sabaeus";
  IF LA >= -30 AND LA <    0 AND LO >= 270 AND LO <  315 THEN Quadrangle = "MC-21: Iapygia";
  IF LA >= -30 AND LA <    0 AND LO >= 225 AND LO <  270 THEN Quadrangle = "MC-22: Mare Tyrrhenum";
  IF LA >= -30 AND LA <    0 AND LO >= 180 AND LO <  225 THEN Quadrangle = "MC-23: Aeolis";
  IF LA >= -65 AND LA <  -30 AND LO >= 120 AND LO <  180 THEN Quadrangle = "MC-24: Phaethontis";
  IF LA >= -65 AND LA <  -30 AND LO >=  60 AND LO <  120 THEN Quadrangle = "MC-25: Thaumasia";
  IF LA >= -65 AND LA <  -30 AND LO >=   0 AND LO <   60 THEN Quadrangle = "MC-26: Argyre";
  IF LA >= -65 AND LA <  -30 AND LO >= 300 AND LO <= 360 THEN Quadrangle = "MC-27: Noachis";
  IF LA >= -65 AND LA <  -30 AND LO >= 240 AND LO <  300 THEN Quadrangle = "MC-28: Hellas";
  IF LA >= -65 AND LA <  -30 AND LO >= 180 AND LO <  240 THEN Quadrangle = "MC-29: Eridania";
  IF LA >= -90 AND LA <  -65 AND LO >=   0 AND LO <= 360 THEN Quadrangle = "MC-30: Mare Australe (South Pole)";

  /* Collapse the Morphology of Eject 1 to its Main Feature, to reduce the output */
  IF (INDEX(MORPHOLOGY_EJECTA_1, "/") = 0)
    THEN MorphoE1 = MORPHOLOGY_EJECTA_1;
    ELSE MorphoE1 = SUBSTR(MORPHOLOGY_EJECTA_1, 1, INDEX(MORPHOLOGY_EJECTA_1, "/") - 1);
  MorphoE1U = UPCASE(TRIM(MorphoE1));

  /* Collapse the Morphology of Eject 2 to its Main Feature, to reduce the output */
  IF (INDEX(MORPHOLOGY_EJECTA_2, "/") = 0)
    THEN MorphoE2 = MORPHOLOGY_EJECTA_2;
    ELSE MorphoE2 = SUBSTR(MORPHOLOGY_EJECTA_2, 1, INDEX(MORPHOLOGY_EJECTA_2, "/") - 1);
  MorphoE2U = UPCASE(TRIM(MorphoE2));

  /* Collapse the Morphology of Eject 3 to its Main Feature, to reduce the output */
  IF (INDEX(MORPHOLOGY_EJECTA_3, "/") = 0)
    THEN MorphoE3 = MORPHOLOGY_EJECTA_3;
    ELSE MorphoE3 = SUBSTR(MORPHOLOGY_EJECTA_3, 1, INDEX(MORPHOLOGY_EJECTA_3, "/") - 1);
  MorphoE3U = UPCASE(TRIM(MorphoE3));

PROC SORT;
  BY CRATER_ID;
/* Calculate Frequencies and Proportions */
PROC FREQ;
  TABLE Hemisphere Quadrangle MorphoE1U MorphoE2U MorphoE3U NUMBER_LAYERS;
RUN;

Output

Hemisphere

Hemisphere	Frequency	Percent	Cumulative Frequency	Cumulative Percent
Equator	7	0.00	7	0.00
North	150887	39.26	150894	39.26
South	233449	60.74	384343	100.00

Quadrangle

Quadrangle	Frequency	Percent	Cumulative Frequency	Cumulative Percent
MC-01: Mare Boreum (North Pole)	6405	1.67	6405	1.67
MC-02: Diacria	9592	2.50	15997	4.16
MC-03: Arcadia	7835	2.04	23832	6.20
MC-04: Mare Acidalium	4436	1.15	28268	7.35
MC-05: Ismenius Lacus	6762	1.76	35030	9.11
MC-06: Casius	9068	2.36	44098	11.47
MC-07: Cebrenia	15028	3.91	59126	15.38
MC-08: Amazonis	16738	4.35	75864	19.74
MC-09: Tharsis	12921	3.36	88785	23.10
MC-10: Lunae Palus	3478	0.90	92263	24.01
MC-11: Oxia Palus	4666	1.21	96929	25.22
MC-12: Arabia	7640	1.99	104569	27.21
MC-13: Syrtis Major	13522	3.52	118091	30.73
MC-14: Amenthes	13937	3.63	132028	34.35
MC-15: Elysium	18866	4.91	150894	39.26
MC-16: Memnonia	20455	5.32	171349	44.58
MC-17: Phoenicis Lacus	14561	3.79	185910	48.37
MC-18: Coprates	5777	1.50	191687	49.87
MC-19: Margaritifer Sinus	17022	4.43	208709	54.30
MC-20: Sinus Sabaeus	17664	4.60	226373	58.90
MC-21: Iapygia	19422	5.05	245795	63.95
MC-22: Mare Tyrrhenum	19977	5.20	265772	69.15
MC-23: Aeolis	18703	4.87	284475	74.02
MC-24: Phaethontis	14786	3.85	299261	77.86
MC-25: Thaumasia	16011	4.17	315272	82.03
MC-26: Argyre	15775	4.10	331047	86.13
MC-27: Noachis	16141	4.20	347188	90.33
MC-28: Hellas	9535	2.48	356723	92.81
MC-29: Eridania	13930	3.62	370653	96.44
MC-30: Mare Australe (South Pol	13690	3.56	384343	100.00

Ejecta Morphology 1 (Group by Main Feature)

MorphoE1U	Frequency	Percent	Cumulative Frequency	Cumulative Percent
DLEPC	495	1.11	495	1.11
DLEPCPD	10	0.02	505	1.13
DLEPD	1	0.00	506	1.13
DLEPS	631	1.41	1137	2.55
DLEPSPD	2	0.00	1139	2.55
DLERC	386	0.86	1525	3.42
DLERCPD	7	0.02	1532	3.43
DLERS	1242	2.78	2774	6.22
DLERSRD	2	0.00	2776	6.22
DLSPC	1	0.00	2777	6.22
MLEPC	22	0.05	2799	6.27
MLEPS	43	0.10	2842	6.37
MLERC	24	0.05	2866	6.42
MLERS	491	1.10	3357	7.52
MLERSRD	1	0.00	3358	7.52
PD	2	0.00	3360	7.53
RD	27069	60.66	30429	68.19
SLEPC	2601	5.83	33030	74.02
SLEPCPD	75	0.17	33105	74.18
SLEPCRD	2	0.00	33107	74.19
SLEPD	44	0.10	33151	74.29
SLEPS	4998	11.20	38149	85.49
SLEPSPD	52	0.12	38201	85.60
SLEPSRD	3	0.01	38204	85.61
SLERC	1280	2.87	39484	88.48
SLERCPD	10	0.02	39494	88.50
SLERS	5111	11.45	44605	99.96
SLERSPD	16	0.04	44621	99.99
SLERSRD	4	0.01	44625	100.00

Frequency Missing = 339718

Ejecta Morphology 2 (Group by Main Feature)

MorphoE2U	Frequency	Percent	Cumulative Frequency	Cumulative Percent
HU	1466	7.53	1466	7.53
HUAM	1373	7.05	2839	14.58
HUBL	4459	22.89	7298	37.47
HUSL	6540	33.58	13838	71.05
HUSP	77	0.40	13915	71.45
SM	805	4.13	14720	75.58
SMAM	844	4.33	15564	79.91
SMBL	1097	5.63	16661	85.55
SMSL	2797	14.36	19458	99.91
SMSP	18	0.09	19476	100.00

Frequency Missing = 364867

Ejecta Morphology 3 (Group by Main Feature)

MorphoE3U	Frequency	Percent	Cumulative Frequency	Cumulative Percent
BUMBLEBEE	18	1.39	18	1.39
BUTTERFLY	76	5.88	94	7.27
INNER IS BUTTERFLY	2	0.15	96	7.42
INNER IS PIN-CUSHION	87	6.73	183	14.15
INNER IS PSEUDO-BUTTERFLY	1	0.08	184	14.23
INNER IS PSEUDO-PIN-CUSHION	1	0.08	185	14.31
INNER IS PSEUDO-SMALL-CROWN	4	0.31	189	14.62
INNER IS SMALL-CROWN	66	5.10	255	19.72
INNER-MOST IS SMALL-CROWN	1	0.08	256	19.80
MIDDLE IS RECTANGULAR	1	0.08	257	19.88
OUTER IS BUTTERFLY	4	0.31	261	20.19
OUTER IS PSEUDO-BUTTERFLY	4	0.31	265	20.49
OUTER IS RECTANGULAR	1	0.08	266	20.57
OUTER IS SPLASH	56	4.33	322	24.90
PIN-CUSHION	351	27.15	673	52.05
PSEDUO-BUTTERFLY	1	0.08	674	52.13
PSEUDO-BUTTERFLY	118	9.13	792	61.25
PSEUDO-PIN-CUSHION	1	0.08	793	61.33
PSEUDO-RECTANGULAR	26	2.01	819	63.34
PSEUDO-SMALL-CROWN	56	4.33	875	67.67
RECTANGULAR	38	2.94	913	70.61
SANDBAR	58	4.49	971	75.10
SMALL-CROWN	267	20.65	1238	95.75
SPLASH	55	4.25	1293	100.00

Frequency Missing = 383050

Maximum Number of Cohesive Layers

NUMBER_LAYERS	Frequency	Percent	Cumulative Frequency	Cumulative Percent
0	364612	94.87	364612	94.87
1	15467	4.02	380079	98.89
2	3435	0.89	383514	99.78
3	739	0.19	384253	99.98
4	85	0.02	384338	100.00
5	5	0.00	384343	100.00

Using Python

Code

"""
Created on Tue Oct 01 01:27:35 2015

@author: angeloklin
"""
# Import libraries
import pandas as pd

# load data
data = pd.read_csv("marscrater_pds.csv", na_values = [" "], low_memory = False)

# function to return hemisphere
def Hemisphere(Latitude):
  if Latitude > 0:
    return "North"
  elif Latitude < 0:
    return "South"
  else:
    return "Equator"

# function to return hemisphere
def Quadrangle(Coordinates):
  la = Coordinates["LATITUDE_CIRCLE_IMAGE"]
  lo = Coordinates["LONGITUDE_CIRCLE_IMAGE"] + 180
  if la >=  65 and la <=  90 and lo >=   0 and lo <= 360: return "MC-01: Mare Boreum (North Pole)"
  if la >=  30 and la <   65 and lo >= 120 and lo <  180: return "MC-02: Diacria"
  if la >=  30 and la <   65 and lo >=  60 and lo <  120: return "MC-03: Arcadia"
  if la >=  30 and la <   65 and lo >=   0 and lo <   60: return "MC-04: Mare Acidalium"
  if la >=  30 and la <   65 and lo >= 300 and lo <= 360: return "MC-05: Ismenius Lacus"
  if la >=  30 and la <   65 and lo >= 240 and lo <  300: return "MC-06: Casius"
  if la >=  30 and la <   65 and lo >= 180 and lo <  240: return "MC-07: Cebrenia"
  if la >=   0 and la <   30 and lo >= 135 and lo <  180: return "MC-08: Amazonis"
  if la >=   0 and la <   30 and lo >=  90 and lo <  135: return "MC-09: Tharsis"
  if la >=   0 and la <   30 and lo >=  45 and lo <   90: return "MC-10: Lunae Palus"
  if la >=   0 and la <   30 and lo >=   0 and lo <   45: return "MC-11: Oxia Palus"
  if la >=   0 and la <   30 and lo >= 315 and lo <= 360: return "MC-12: Arabia"
  if la >=   0 and la <   30 and lo >= 270 and lo <  315: return "MC-13: Syrtis Major"
  if la >=   0 and la <   30 and lo >= 225 and lo <  270: return "MC-14: Amenthes"
  if la >=   0 and la <   30 and lo >= 180 and lo <  225: return "MC-15: Elysium"
  if la >= -30 and la <    0 and lo >= 135 and lo <  180: return "MC-16: Memnonia"
  if la >= -30 and la <    0 and lo >=  90 and lo <  135: return "MC-17: Phoenicis Lacus"
  if la >= -30 and la <    0 and lo >=  45 and lo <   90: return "MC-18: Coprates"
  if la >= -30 and la <    0 and lo >=   0 and lo <   45: return "MC-19: Margaritifer Sinus"
  if la >= -30 and la <    0 and lo >= 315 and lo <= 360: return "MC-20: Sinus Sabaeus"
  if la >= -30 and la <    0 and lo >= 270 and lo <  315: return "MC-21: Iapygia"
  if la >= -30 and la <    0 and lo >= 225 and lo <  270: return "MC-22: Mare Tyrrhenum"
  if la >= -30 and la <    0 and lo >= 180 and lo <  225: return "MC-23: Aeolis"
  if la >= -65 and la <  -30 and lo >= 120 and lo <  180: return "MC-24: Phaethontis"
  if la >= -65 and la <  -30 and lo >=  60 and lo <  120: return "MC-25: Thaumasia"
  if la >= -65 and la <  -30 and lo >=   0 and lo <   60: return "MC-26: Argyre"
  if la >= -65 and la <  -30 and lo >= 300 and lo <= 360: return "MC-27: Noachis"
  if la >= -65 and la <  -30 and lo >= 240 and lo <  300: return "MC-28: Hellas"
  if la >= -65 and la <  -30 and lo >= 180 and lo <  240: return "MC-29: Eridania"
  if la >= -90 and la <  -65 and lo >=   0 and lo <= 360: return "MC-30: Mare Australe (South Pole)"

# function to get the morphology's main feature
def MainMorpho(Morpho):
  if pd.isnull(Morpho):
    return Morpho
  foundAt = Morpho.find("/")
  if foundAt >= 0:
    m = Morpho[0:foundAt]
  else:
    m = Morpho
  return m.strip().upper()

print("Mars Craters' data set summary:")
print("- Number of observations(rows): ", len(data))
print("- Number of variables(columns): ", len(data.columns))
print("")

print("Hemispheres:")
Hemispheres = data["LATITUDE_CIRCLE_IMAGE"].map(lambda lat: Hemisphere(lat))
freq = Hemispheres.value_counts(sort = True)
prop = Hemispheres.value_counts(sort = True, normalize = True)
print("- Missing Values: ", Hemispheres.isnull().sum())
print("- Frequency Table: ")
print("|            | Frequency | Proportion |")
for i in range(len(freq)):
  print("|", format(freq.index[i], "<10s"), "|   ", format(freq[i], ">6d"), "|    ", format(prop[i], ">.4f"), "|")
print("")

print("Quadrangles:")
Quadrangles = data.loc[:, "LATITUDE_CIRCLE_IMAGE":"LONGITUDE_CIRCLE_IMAGE"].apply(Quadrangle, axis = 1)
freq = Quadrangles.value_counts(sort = True)
prop = Quadrangles.value_counts(sort = True, normalize = True)
print("- Missing Values: ", Quadrangles.isnull().sum())
print("- Frequency Table: ")
print("|                                     | Frequency | Proportion |")
for i in range(len(freq)):
  print("|", format(freq.index[i], "<35s"), "|   ", format(freq[i], ">6d"), "|    ", format(prop[i], ">.4f"), "|")
print("")

print("Ejecta Morphology 1 (Group by Main Feature):")
MorphoE1 = data["MORPHOLOGY_EJECTA_1"].map(lambda morpho: MainMorpho(morpho))
MorphoE1a = MorphoE1[MorphoE1.notnull()]
freq = MorphoE1a.value_counts(sort = True)
prop = MorphoE1a.value_counts(sort = True, normalize = True, dropna = False)
print("- Missing Values: ", MorphoE1.isnull().sum())
print("- Frequency Table: ")
print("|            | Frequency | Proportion |")
for i in range(len(freq)):
  print("|", format(freq.index[i], "<10s"), "|   ", format(freq[i], ">6d"), "|    ", format(prop[i], ">.4f"), "|")
print("")

print("Ejecta Morphology 2 (Group by Main Feature):")
MorphoE2 = data["MORPHOLOGY_EJECTA_2"].map(lambda morpho: MainMorpho(morpho))
MorphoE2a = MorphoE2[MorphoE2.notnull()]
freq = MorphoE2a.value_counts(sort = True)
prop = MorphoE2a.value_counts(sort = True, normalize = True, dropna = False)
print("- Missing Values: ", MorphoE2.isnull().sum())
print("- Frequency Table: ")
print("|            | Frequency | Proportion |")
for i in range(len(freq)):
  print("|", format(freq.index[i], "<10s"), "|   ", format(freq[i], ">6d"), "|    ", format(prop[i], ">.4f"), "|")
print("")

print("Ejecta Morphology 3 (Group by Main Feature):")
MorphoE3 = data["MORPHOLOGY_EJECTA_3"].map(lambda morpho: MainMorpho(morpho))
MorphoE3a = MorphoE3[MorphoE3.notnull()]
freq = MorphoE3a.value_counts(sort = True)
prop = MorphoE3a.value_counts(sort = True, normalize = True, dropna = False)
print("- Missing Values: ", MorphoE3.isnull().sum())
print("- Frequency Table: ")
print("|                              | Frequency | Proportion |")
for i in range(len(freq)):
  print("|", format(freq.index[i], "<28s"), "|   ", format(freq[i], ">6d"), "|    ", format(prop[i], ">.4f"), "|")
print("")


print("Maximum Number of Cohesive Layers:")
freq = data["NUMBER_LAYERS"].value_counts(sort = False)
prop = data["NUMBER_LAYERS"].value_counts(sort = False, normalize = True)
print("- Missing Values: ", data["NUMBER_LAYERS"].isnull().sum())
print("- Frequency Table: ")
print("|        | Frequency | Proportion |")
for i in range(len(freq)):
  print("|", format(freq.index[i], "<6d"), "|   ", format(freq[i], ">6d"), "|    ", format(prop[i], ">.4f"), "|")
print("")

Output

Mars Craters’ data set summary:

Number of observations(rows): 384343
Number of variables(columns): 10

Hemisphere

Missing Values: 0

Frequency Table:

	Frequency	Proportion
South	233449	0.6074
North	150887	0.3926
Equator	7	0.0000

Quadrangle

Missing Values: 0

Frequency Table:

	Frequency	Proportion
MC-16: Memnonia	20455	0.0532
MC-22: Mare Tyrrhenum	19977	0.0520
MC-21: Iapygia	19422	0.0505
MC-15: Elysium	18866	0.0491
MC-23: Aeolis	18703	0.0487
MC-20: Sinus Sabaeus	17664	0.0460
MC-19: Margaritifer Sinus	17022	0.0443
MC-08: Amazonis	16738	0.0435
MC-27: Noachis	16141	0.0420
MC-25: Thaumasia	16011	0.0417
MC-26: Argyre	15775	0.0410
MC-07: Cebrenia	15028	0.0391
MC-24: Phaethontis	14786	0.0385
MC-17: Phoenicis Lacus	14561	0.0379
MC-14: Amenthes	13937	0.0363
MC-29: Eridania	13930	0.0362
MC-30: Mare Australe (South Pole)	13690	0.0356
MC-13: Syrtis Major	13522	0.0352
MC-09: Tharsis	12921	0.0336
MC-02: Diacria	9592	0.0250
MC-28: Hellas	9535	0.0248
MC-06: Casius	9068	0.0236
MC-03: Arcadia	7835	0.0204
MC-12: Arabia	7640	0.0199
MC-05: Ismenius Lacus	6762	0.0176
MC-01: Mare Boreum (North Pole)	6405	0.0167
MC-18: Coprates	5777	0.0150
MC-11: Oxia Palus	4666	0.0121
MC-04: Mare Acidalium	4436	0.0115
MC-10: Lunae Palus	3478	0.0090

Ejecta Morphology 1 (Group by Main Feature)

Missing Values: 339718

Frequency Table:

	Frequency	Proportion
RD	27069	0.6066
SLERS	5111	0.1145
SLEPS	4998	0.1120
SLEPC	2601	0.0583
SLERC	1280	0.0287
DLERS	1242	0.0278
DLEPS	631	0.0141
DLEPC	495	0.0111
MLERS	491	0.0110
DLERC	386	0.0086
SLEPCPD	75	0.0017
SLEPSPD	52	0.0012
SLEPD	44	0.0010
MLEPS	43	0.0010
MLERC	24	0.0005
MLEPC	22	0.0005
SLERSPD	16	0.0004
SLERCPD	10	0.0002
DLEPCPD	10	0.0002
DLERCPD	7	0.0002
SLERSRD	4	0.0001
SLEPSRD	3	0.0001
SLEPCRD	2	0.0000
DLEPSPD	2	0.0000
DLERSRD	2	0.0000
PD	2	0.0000
DLEPD	1	0.0000
DLSPC	1	0.0000
MLERSRD	1	0.0000

Ejecta Morphology 2 (Group by Main Feature)

Missing Values: 364867

Frequency Table:

	Frequency	Proportion
HUSL	6540	0.3358
HUBL	4459	0.2289
SMSL	2797	0.1436
HU	1466	0.0753
HUAM	1373	0.0705
SMBL	1097	0.0563
SMAM	844	0.0433
SM	805	0.0413
HUSP	77	0.0040
SMSP	18	0.0009

Ejecta Morphology 3 (Group by Main Feature)

Missing Values: 383050

Frequency Table:

	Frequency	Proportion
PIN-CUSHION	351	0.2715
SMALL-CROWN	267	0.2065
PSEUDO-BUTTERFLY	118	0.0913
INNER IS PIN-CUSHION	87	0.0673
BUTTERFLY	76	0.0588
INNER IS SMALL-CROWN	66	0.0510
SANDBAR	58	0.0449
PSEUDO-SMALL-CROWN	56	0.0433
OUTER IS SPLASH	56	0.0433
SPLASH	55	0.0425
RECTANGULAR	38	0.0294
PSEUDO-RECTANGULAR	26	0.0201
BUMBLEBEE	18	0.0139
OUTER IS BUTTERFLY	4	0.0031
OUTER IS PSEUDO-BUTTERFLY	4	0.0031
INNER IS PSEUDO-SMALL-CROWN	4	0.0031
INNER IS BUTTERFLY	2	0.0015
INNER-MOST IS SMALL-CROWN	1	0.0008
OUTER IS RECTANGULAR	1	0.0008
INNER IS PSEUDO-BUTTERFLY	1	0.0008
MIDDLE IS RECTANGULAR	1	0.0008
PSEUDO-PIN-CUSHION	1	0.0008
INNER IS PSEUDO-PIN-CUSHION	1	0.0008
PSEDUO-BUTTERFLY	1	0.0008

Maximum Number of Cohesive Layers

Missing Values: 0

Frequency Table:

	Frequency	Proportion
0	364612	0.9487
1	15467	0.0402
2	3435	0.0089
3	739	0.0019
4	85	0.0002
5	5	0.0000

Mars Craters - Looking for major events - Second Programs

Can crater’s records help to understand Mars’ history?

Angelo Klin

01 October 2015

Summary

Exploratory Data Analysis

Source

Size

Univariate Analysis

Hemisphere

Quadrangle

Ejecta Morphology 1 (Group by Main Feature)

Ejecta Morphology 2 (Group by Main Feature)

Ejecta Morphology 3 (Group by Main Feature)

Maximum Number of Cohesive Layers

Using SAS

Code

Output

Hemisphere

Quadrangle

Ejecta Morphology 1 (Group by Main Feature)

Ejecta Morphology 2 (Group by Main Feature)

Ejecta Morphology 3 (Group by Main Feature)

Maximum Number of Cohesive Layers

Using Python

Code

Output

Hemisphere

Quadrangle

Ejecta Morphology 1 (Group by Main Feature)

Ejecta Morphology 2 (Group by Main Feature)

Ejecta Morphology 3 (Group by Main Feature)

Maximum Number of Cohesive Layers